| Title | Authors | Abstract | Year |
|---|---|---|---|
| Stable data‐driven Koopman predictive control: Concentrated solar collector field case study | Tahereh Gholaminejad, Ali Khaki‐Sedigh | Non‐linearity is an inherent feature of practical systems. Although there have been significant advances in the control of nonlinear systems, the proposed methods often require considerable computational resources or rely on local linearization around equilibrium points. The Koopman operator is an infinite‐dimensional linear operator that fully captures a system’s non‐linear dynamics. However, one of the major problems is identifying a Koopman finite dimensional linear model for a nonlinear system. Initiated by the Willems’ fundamental Lemma, a class of data‐driven control methods has been developed for linear systems without the need to identify the system’s matrices. Motivated by these two ideas, a data‐driven Koopman‐based predictive control scheme for non‐linear systems is proposed for unknown disturbed non‐linear systems utilising a finite‐length dataset. Then, considering the uncertainty in the … | 2023 |
| Robust H∞ tracking of linear discrete‐time systems using Q‐learning | Amir Parviz Valadbeigi, Zhan Shu, Ali Khaki Sedigh | This paper deals with a robust H∞$$ {H}_{\infty } $$ tracking problem with a discounted factor. A new auxiliary system is established in terms of norm‐bounded time‐varying uncertainties. It is shown that the robust discounted H∞$$ {H}_{\infty } $$ tracking problem for the auxiliary system solves the original problem. Then, the new robust discounted H∞$$ {H}_{\infty } $$ tracking problem is represented as a well‐known zero‐sum game problem. Moreover, the robust tracking Bellman equation and the robust tracking Algebraic Riccati equation (RTARE) are inferred. A lower bound of a discounted factor for stability is obtained to assure the stability of the closed‐loop system. Based on the auxiliary system, the system is reshaped in a new structure that is applicable to Reinforcement Learning methods. Finally, an online Q‐learning algorithm without the knowledge of system matrices is proposed to solve the algebraic … | 2023 |
| Online data‐driven control of variable speed wind turbines using the simultaneous perturbation stochastic approximation approach | Mojtaba Nouri Manzar, A Khaki‐Sedigh | This article presents a data‐driven control algorithm for a variable‐speed wind turbine in the partial load region. The controller is designed and optimized online to capture maximum energy from the wind. The online optimization is based on the simultaneous perturbation stochastic approximation method (SPSA) that is data‐driven, has a low computational load, and converges rapidly. In the control structure, the generator torque control is activated, and the aerodynamical models and the wind speed value are not required. A suitable cost function is defined, and a time window optimization problem is solved via the SPSA algorithm. The efficiency of the proposed method is evaluated on a 4.8 MW wind turbine benchmark. | 2023 |
| Kalman Filter Fusion With Smoothing for a Process With Continuous-Time Integrated Sensor | Shirin Movassagh, Alireza Fatehi, Ali Khaki Sedigh, Ala Shariati | Integrated sensor is a well-known methodology of slow sampling rates in chemical processes, which gradually collects material samples within a finite period. This type of infrequent measurement specified for quality variables is a function of states over sampling time. Our objective is to solve the problem of estimating states in fast sampling rates for a continuous-time system in the presence of a slow-rate integrated sensor. For this purpose, two reformulated models are suggested for describing the system, while they do not explicitly include the integral term. Integrated measurement Kalman filter (IMKF) for these two models is presented by the extension of the classical continuous-discrete (CD) kalman filter (KF) to the integrated systems. Then, a novel sliding window smoothing algorithm is proposed for integrated systems using pseudo-estimations of the output, past time information of the fast-rate estimates, and the … | 2023 |
| Corrigendum to “Stable deep Koopman model predictive control for solar parabolic-trough collector field”[Renew. Energy 198 (October 2022) 492–504] | Tahereh Gholaminejad, Ali Khaki-Sedigh | We sincerely regret that there was an error in the published version of our paper. Unfortunately, the content of Algorithms 1 and 2 was misplaced, causing them to appear in incorrect sections. | 2023 |
| Adaptive multi-objective control allocation with online actuator selection for over-actuated systems | Seyyed Reza Jafari, Ali Khaki-Sedigh, Wolfgang Birk | This paper presents an adaptive control allocation technique for over-actuated systems. The online actuator selection algorithm is used to select the best group of actuators. Also, a multi-objective cost function is utilized for the allocation unit. The virtual and actual control signals in the control allocation methodologies are linked by the effectiveness matrix. In many practical systems, the elements of the effectiveness matrix may vary due to changing operating conditions, nonlinearities, ageing, disturbances and faults. Hence, an online algorithm for estimation of the entries of the effectiveness matrix is presented in this paper. Estimation of the effectiveness matrix will be used for the proposed adaptive actuator selection strategy, employing the Actuator Effectiveness Index (AEI). The AEI is calculated for all the actuators, and the best group of actuators will be subsequently selected. Finally, simulation results are used to … | 2023 |
| Parameter and State Estimation of Managed Pressure Drilling System Using the Optimization-Based Supervisory Framework | Amirmasoud Molaei, Amirhossein Nikoofard, Ali Khaki Sedigh, Lars Imsland | This brief proposes a method for the simultaneous estimation of unknown parameters and unmeasured states of nonlinear continuous-time systems. The proposed methodology has been inspired by the supervisory estimation approaches that use a bank of observers and are designed based on a set of fixed nominal parameter values. Consequently, the methods have a high computational load, and the estimated parameters marginally converge to the true parameters. For the reduction of computational load, a new objective function with a lower computational load that is computed during a sliding time window is proposed. Then, an observer with an optimization-based framework is introduced for nonlinear systems with affine unknown parameters, that replaces the bank of observers with a single observer. The unknown parameters update is based on the defined objective function. The performance of the method … | 2023 |
| Estimation and stochastic control of nonlinear dynamic systems over the AWGN channel: Application in tele‐presence and tele‐operation of autonomous vehicles | Somayeh Dolatkhah Takloo, Alireza Farhadi, Ali Khaki‐Sedigh | This paper is concerned with tele‐presence and tele‐operation of autonomous vehicles over the Additive White Gaussian Noise (AWGN) channel. This wireless communication channel is subject to transmission noise and transmission power constraint. An encoder, decoder and controller are proposed by implementing a novel linearization method for linearizing the nonlinear dynamic systems at operating points. For the linearized systems, the encoder, decoder and controller are implemented that were previously proposed for output tracking as well as stability of linear dynamic systems. Two novel linearization methods are proposed and their satisfactory performances are proved for output tracking as well as stability of nonlinear dynamic system. The first method is based on the fixed linearization rate and the second one is based on the variable (optimal) linearization rate. The decoder that is based on the second … | 2023 |
| An Analytical Solution to the Inverse Kinematic Problem, Dynamic Modeling, and Control of a 3 DOF Pedestal for Track Flying Targets | Ali Akbar Sadeghi, Ahmad Reza Vali, Ali Khaki Sedigh | In this paper, a three DOF (Degree Of Freedom) aerial target tracking pedestal that covers the entirety of the 3D threat space is introduced. The conventional two DOF tracking pedestals cannot track some trajectories due to having singular points in their workspace. The extra DOF in a three DOF tracking pedestal overcomes this problem. Moreover, the redundant DOF reduces the needed joint velocity and acceleration in the tracking process and makes the whole structure more maneuverable. The challenging matter in utilizing such a redundant pedestal is that the Inverse Kinematic Problem (IKP) has infinite sets of solutions. An analytical solution is proposed to handle this problem which results in a single set of solutions. Furthermore, the dynamic model of the pedestal is derived using the Euler-Lagrange method, and the verification is performed using mechanical design software. Finally, to demonstrate the effectiveness of the proposed pedestal in tracking aerial targets with unknown trajectories, a PID controller and an LQR controller are utilized in simulations. The results yield that tracking any complex trajectory is attainable using conventional controllers. | 2023 |
| Stable deep Koopman model predictive control for solar parabolic-trough collector field | Tahereh Gholaminejad, Ali Khaki-Sedigh | Concentrated Solar Power plants (CSP) have the energy storage capability to generate electricity when sunlight is scarce. However, due to the highly non-linear dynamics of these systems, a simple linear controller will not be able to overcome the variable dynamics and multiple disturbance sources affecting it. In this paper, a deep Model Predictive Control (MPC) based on the Koopman operator is proposed and applied to control the Heat Transfer Fluid (HTF) temperature of a distributed-parameter model of the ACUREX solar collector field located at Almería, Spain. The Koopman operator is an infinite-dimensional linear operator that fully captures a system’s non-linear dynamics through the linear evolution of functions of the state-space. However, one of the major problems is identifying a Koopman linear model for a non-linear system. Koopman eigenfunctions are involved in converting a non-linear model to a … | 2022 |
| Control of managed pressure drilling systems using nonlinear predictive generalized minimum variance approach based on a Volterra model | Mohammad Amin Sheikhi, Amirhossein Nikoofard, Ali Khaki-Sedigh | This paper proposes a nonlinear predictive generalized minimum variance (NPGMV) control scheme for automatic control of the managed pressure drilling (MPD) systems in the presence of disturbances. Since the exact model of the system is not usually available in practice, the hydraulic flow model of MPD is described by an autoregressive second-order Volterra model. The conventional least-squares method is applied to input–output data, thereby identifying the Volterra model. Bottom-hole pressure regulation and kick handling are achieved through the control scheme. To deal with a reservoir kick, the proposed method switches to flow control mode automatically, and prevents the reservoir fluid influx into the well surface. The proposed method also has the capability to keep the bottom-hole pressure above the reservoir pressure during a formidable scenario such as pipe connection. In addition, the robustness … | 2022 |
| Eigenvalue sensitivity-based analysis for evaluation of biological network stability versus disturbances | Maryam Gholampour, Ali Khaki Sedigh, Mohammad Ghassem Mahjani, Abdorasoul Ghasemi | Network modeling is an effective tool for understanding the properties of complex systems. Networks are widely used to help us gain insight into biological systems. In this way, the cell, gene, and protein are denoted as nodes, and the connection elements are regarded as links or edges. In this paper, a novel stochastic strategy is developed for identifying the most influential edges on the stability of biological networks. Regarding the principles of networks and control-theory basics like Jacobian and eigenvalue sensitivity-based analysis, a new criterion is proposed, called “random sensitivity index matrix” (RSIM). RSIM evaluates the eigenvalue sensitivity of all edges in a network in the presents of stochastic disturbances based on the Monte Carlo algorithm. Through the values of RSIM elements, the sensitive edges are identifiable. In addition, the contribution of each edge in network instability has been compared … | 2022 |
| Online data-driven control of variable speed wind turbines using the simultaneous perturbation stochastic approximation approach | Mojtaba Nouri Manzar, A Khaki-Sedigh | This article presents a data-driven control algorithm for a variable-speed wind turbine in the partial load region. The controller is designed and optimized online to capture maximum energy from the wind. The online optimization is based on the simultaneous perturbation stochastic approximation method (SPSA) that is data-driven, has a low computational load, and converges rapidly. In the control structure, the generator torque control is activated, and the aerodynamical models and the wind speed value are not required. A suitable cost function is defined, and a time window optimization problem is solved via the SPSA algorithm. The efficiency of the proposed method is evaluated on a 4.8 MW wind turbine benchmark. | 2022 |
| Control and measurement of nonlinear dynamic systems over AWGN channel with application in tele-operation of autonomous vehicles | Somayeh Dolatkhah Takloo, Alireza Farhadi, Ali Khaki-Sedigh | This paper is concerned with state tracking as well as reference tracking of noisy nonlinear dynamic systems over Additive White Gaussian Noise (AWGN) channel, which is subject to transmission noise imperfection and transmission power constraint. In order to address these problems, in this paper we implement a suitable linearization method. Using this method, we linearize the nonlinear dynamic system around working points and for linearized systems, we present proper encoder and decoder for tracking the state trajectory of nonlinear dynamic systems at the end of communication link when sensor measurements are sent through the AWGN channel subject to imperfection and constraint. The satisfactory performance of the proposed state and reference tracking techniques are illustrated via computer simulations by applying these techniques on the unicycle model, which is an abstract representation for the … | 2022 |
| Design and implementation of a fault-tolerant controller using control allocation techniques in the presence of actuators saturation for a VTOL octorotor | Hamid Hafezi, Ali Bakhtiari, Ali Khaki-Sedigh | Fault-tolerant control systems are vital in many industrial systems. Actuator redundancy is employed in advanced control strategies to increase system maneuverability, flexibility, safety, and fault tolerability. In this paper, a fault-tolerant control scheme is proposed to make an over-actuated octorotor robust, against actuators fault and saturation. A sliding mode observer is employed to determine the actuators condition. Then, a fault-tolerant control based on the control allocation methodology is proposed to distribute the control signals between the actuators by considering their condition. In a nonlinear system, an actuator fault can lead to the saturation of other actuators and steady-state errors that can cause closed-loop instability. Hence, the proposed control scheme corrects the actuator signals in a way that their limitations are considered. Finally, experimental studies are carried out and a comparison study is … | 2022 |
| رفع تکینگی در ردیابی اهداف هوایی با استفاده از سکوی سه درجه آزادی | صادقی, ولی, خاکی صدیق | ردیابی اهداف هوایی برای برخی از مسیرها توسط سکوهای دو درجه آزادی معمول، مستلزم تولید سرعت و شتابهای بسیار بالا است که از آن بهعنوان تکینگی یاد میگردد. برای رفع این مشکل یک سکوی سه درجه آزادی که دارای یک درجه افزونگی است، پیشنهاد میشود. ایجاد افزونگی در این سکو، علاوه بر افزایش مانورپذیری و بهبود عملکرد ردیابی، امکان عبور از نقاط تکین معمول در ساختارهای دو درجه آزادی را بدون نیاز به تولید سرعت و شتابهای بالا در محورهای حرکتی سکو ممکن میکند. چالشی که سکوی سه درجه آزادی پیشنهادی با آن روبرو است، عدم وجود جواب یکتا برای حل مسئله سینماتیک معکوس این سکو است. در این مقاله برای رفع چالش سینماتیک معکوس سکوی سه درجه آزادی دارای افزونگی، دو روش مبتنی بر کمینهسازی سرعت و شتاب محورهای حرکتی سکو پیشنهاد و با روش مرسوم شبه معکوس ژاکوبی مقایسه شدهاند. در روش کمینهسازی سرعت، تابع هزینه مناسبی متشکل از خطای ردیابی و سرعت محورها به کار گرفته شده است. در روش کمینهسازی شتاب نیز تابع هزینهای … | 2022 |
| Robust Decentralized Control System Design based on Nash Equilibrium Point using Linear Quadratic Regulators | S Najafi Birgani, B Moaveni, A Khaki-Sedigh | Non-cooperative intelligent control agents (ICAs) with dedicated cost functions, can lead the system to poor performance and in some cases, closed-loop instability. A robust solution to this challenge is to place the ICAs at the feedback Nash equilibrium point (FNEP) of the differential game between them. This paper introduces the designation of a robust decentralized infinite horizon LQR control system based on the FNEP for a linear time-invariant system. For this purpose, two control strategies are defined. The first one is a centralized infinite horizon LQR (CIHLQR) problem (i.e. a supervisory problem), and the second one is a decentralized control problem (i.e. an infinite horizon linear-quadratic differential game). Then, while examining the optimal solution of each of the above strategies on the performance of the other, the necessary and sufficient conditions for the equivalence of the two problems are presented … | 2022 |
| Nonlinear analysis and minimum L2-norm control in memcapacitor-based hyperchaotic system via online particle swarm optimization | F Setoudeh, A Khaki Sedigh | Memristor and memcapacitor are two novel memristive devices. Memristive nonlinear elements behave like synapses in the nervous system. In this study, an original physical model of HP memristor is presented based on the movement of the boundary between the doped and undoped regions by causing the charged dopants to drift. Furthermore, a charge-controlled memcapacitor is used to design a novel hyperchaotic oscillator. It is found that the hyperchaotic oscillator, which is based on memristor and memcapacitor, can realize high-security data encryption. Then, the problem of controlling chaos is addressed in the proposed memcapacitor-based hyperchaotic memristor oscillator using a simple feedback control. Moreover, in this study, a novel approach is used to stabilize chaos using the L2–norm minimization method. The feedback control is applied to minimize the L2–norm of state variables as the cost … | 2021 |
| Predictive-based sliding mode control for mitigating torsional vibration of drill string in the presence of input delay and external disturbance | Roya Sadeghimehr, Amirhossein Nikoofard, Ali Khaki Sedigh | Dealing with torsional vibrations and stick–slip oscillations of a drill string system is a challenging engineering task in the oil drilling process because of the harmful and costly consequences of such vibrations. In this article, the drill string system is modeled using a lumped-parameter model with four degrees of freedom, and the bit–rock contact is represented by a nonlinear function of a bit velocity. Also, tracking the desired velocity of a drill string system with known constant input delay is addressed in the presence of external disturbance and parameter uncertainties by applying the Smith predictor–based sliding mode control method. The performance of the smith predictor–based sliding mode control with input delay and disturbance in tracking the desired velocity and controlling the stick–slip oscillations is compared with the sliding mode control with/without input delay. The system output’s sensitivity to the delay … | 2021 |
| Multiple model unfalsified adaptive generalized predictive control based on the quadratic inverse optimal control concept | Bahman Sadeghi Forouz, Mojtaba Nouri Manzar, Ali Khaki‐Sedigh | Unfalsified adaptive control (UAC) is a class of switching control systems which deals with the control of uncertain systems. The UAC includes a bank of controllers, a supervisor, and a system in which the supervisor selects a stabilizing controller based on the system input and output data. Feasibility is the only assumption required in the UAC strategy, which guarantees that there is at least one stabilizing controller in the controller bank. UAC uses the cost detectability definition to prove closed‐loop stability. The combination of UAC and multiple model supervisory adaptive control (MMASC) results in the proposed unfalsified multi‐model control methodology that enjoys appropriate transient performance and stability proof with required minimum assumptions. In practical controller implementations, the effect of actuator constraints on the control signals is crucial. Despite the significance of constrained systems … | 2021 |
| Minimum variance control of chaos in a hyperchaotic memristor based oscillator using online particle swarm optimization | Farbod Setoudeh, Ali Khaki Sedigh | This paper introduces a new hyperchaotic oscillator base on a new boundary-restricted Hewlett-Packard memristor model. Firstly, the complex system is designed based on a memristor-based hyperchaotic real system, and its properties are analyzed by means of Lyapunov exponents, Lyapunov dimension and phase portraits diagrams. Secondly, a simple feedback control based on the minimum variance control technique is designed to stabilize the hyperchaotic oscillator system, which is one of the new developed approaches for controlling the chaos in high-dimensional hyperchaotic systems. In this method, the time series variance is considered for designing and calculating the state feedback control gain. Furthermore, the state feedback control is designed so that to minimize the variance as a cost function, followed by developing an online optimization technique using the particle swarm optimization method in … | 2021 |
| Leader–follower consensus control for a nonlinear multi-agent robot system with input saturation and external disturbance | Majid Naserian, Amin Ramazani, Ali Khaki-Sedigh, Ali Moarefianpour | This paper addresses the leader–follower consensus control problem for a nonlinear multi-agent robot system with control input constraint and external disturbances. Robot system is one of the most important practical systems in the industry. Due to the presence of disturbances in most practical systems, this paper considers the issue of finite-time leader–follower consensus control of the nonlinear multi-agent robot system along with actuator saturation and bounded disturbance. The modified terminal sliding mode control method is suggested for the system which is able to guarantee the stability of the overall system and fast finite-time leader–follower consensus control. For two different scenarios, the simulation of multi-agent robot system has been performed. The results show the effectiveness of the proposed control method. | 2021 |
| Design of nonlinear predictive generalized minimum variance control for performance monitoring of nonlinear control systems | Mohammad Amin Sheikhi, Ali Khaki-Sedigh, Amirhossein Nikoofard | In this paper, a nonlinear predictive generalized minimum variance (NPGMV) controller is proposed and explicitly formulated for a class of nonlinear systems modeled by autoregressive second-order Volterra series, applying the polynomial approach. Hence, a new benchmark controller for performance assessment is introduced to improve the achievable control performance. Furthermore, to have an efficient control assessment, a data-driven algorithm based on the NPGMV control is presented that uses only the closed-loop operating data. In the design procedure, a multi-step cost function is defined to incorporate predictive action. Exploiting the predictive control concept enables the control scheme to handle constrained problems. Also, the proposed control algorithm utilizes an inherent integrating effect, which is essential for practical purposes. Volterra series are employed for modeling and identification of the … | 2021 |
| Cooperative Robust H-∞ Output Consensus in Continuous-Time Heterogeneous Multi-Agent Systems Using Integral Reinforcement Learning Method | Amir Parviz Valadbeigi, Ali Khaki Sedigh, Frank Lewis, Ali Moarefian Poor | : The Robust Cooperative Output Consensus (RCOC) in continuous time Heterogeneous Multi-Agent Systems with the directed graph is addressed. In the standard solution of the RCOC, the p-copy internal model method is used. This method requires dynamical equations of the agents and the leader. In the present paper, based on the equivalent auxiliary system method, a new auxiliary system is obtained. Then, the RCOC is transformed to a control problem. Moreover, a model-free algorithm is proposed to solve the Robust Algebraic Riccati Equation using the Integral Reinforcement Learning (IRL) method. It is shown that the proposed method satisfies the output regulation equations. A simulation example verifies the effectiveness of the proposed method. | 2021 |
| Adaptive control of large-scale systems with long input and state delays and time-varying delays in the uncertain nonlinear interconnections | SH Hashemipour, N Vasegh, A Khaki Sedigh | In recent years, the increasing size of systems, their connections, and the increasing use of networks are a major challenge in their decentralized control. The main problems in controlling these types of systems are the uncertainty of the interconnection terms and the uncertainty and time-varying communication delays between the subsystems. The existence of delay in local controller and states can make controlling these types of systems more difficult. These delays in the subsystems can be assumed known and constant since local dynamics can be available. In this chapter, we design a decentralized model reference adaptive control for this class of large-scale systems with long input and state delays and time-varying delays in the uncertain nonlinear interconnection terms. For compensation of the input delay, we introduce some methods such as a nested predictor and chains of integrators. To solve the … | 2021 |
| Robustness analysis and design of fractional order Iλ Dμ controllers using the small gain theorem | Roohallah Azarmi, Mahsan Tavakoli-Kakhki, Alireza Fatehi, Ali Khaki Sedigh | In this paper, a simple method is proposed to tune the parameters of Fractional Integral-Fractional Derivative (FIFE) Iλ Dμ controllers based on the Bode diagram. The proposed technique provides a practical approach for tuning FIFE controllers to compensate stable plants. Using the small gain theorem and based on the sensitivity functions analysis, it is proved that by applying the designed FIFE controller the robustness of the compensated system in the presence of plant uncertainties is improved in comparison to the PI controller in a similar structure. Moreover, the closed-loop phase margin and gain crossover frequency are adjustable by tuning the free controller parameters. Simulation results are presented to demonstrate the simplicity of application and effectiveness of the tuned controller. | 2020 |
| Control of large scale interconnected systems with input and state delays using decentralized adaptive state observers | Seyed Hamid Hashemipour, Nastaran Vasegh, Ali Khaki Sedigh | This paper investigates the problem of decentralized model reference adaptive control (MRAC) for a class of large scale interconnected systems with both state and input delays. The upper bounds of the interconnection terms are considered to be unknown. Time varying delays in the nonlinear interconnection terms are bounded and nonnegative continuous functions and their derivatives are not necessarily less than one. For exact prediction, a decentralized adaptive state observer is designed and a nested predictor based approach is established to predict the future states of the input delay compensation. It is shown that the solutions of uncertain large‐scale time‐delay interconnected systems converge uniformly exponentially to a desired small ball. The effectiveness of the proposed approaches is illustrated by two examples. | 2020 |
| Fast terminal sliding mode control for a nonlinear multi-agent robot system with disturbance | Majid Naserian, Amin Ramazani, Ali Khaki-Sedigh, Ali Moarefianpour | This paper addresses the consensus control problem for a nonlinear multi-agent robot system in the presence of external disturbances. Robot system is one of the most important practical systems in the industry. Because of the presence of disturbances in most practical systems, this paper considers the issue of finite-time consensus control of the nonlinear multi-agent robot system in the presence of unknown bounded disturbance. The modified terminal sliding mode control method is suggested for the system which is able to guarantee the stability of the overall system and fast finite-time consensus control purpose. In two different scenarios, the simulation of multi-agent robot system has been performed. The results show the effectiveness of the proposed control method on the multi-agent robot system. | 2020 |
| Leading Higher Education in Iran during COVID-19 Pandemic: Reporting the Policies and Progresses | Ali Khaki Sedigh, Mohamad Reza Ahanchian | Background After the COVID-19 pandemic and the consequent restrictions assigned by the National Committee on Combating Coronavirus (NCCC), the Ministry of Science, Research, and Technology (MSRT) set up committees to trace and analyze the outcomes of the pandemic. Objectives This paper aimed to explain the policies, programs, and activities executed by MSRT and analyze the points of strength and weakness. Methods In this report, the MSRT experience during the first wave of the COVID-19 pandemic in the Iran higher education (HE) system is briefly reported by referring to pieces of evidence documented by MSRT and analyzing strengths and, predicting the outcomes toward the future. The evidence was analyzed descriptively. Results The policies, plans, and actions were based on three key policies including participation, adaptation, and tolerance. Conclusion Iranian HE system has changed in many aspects during the recent months due to the COVID-19 pandemic. MSRT instantly reorganized its activities to coordinate its decisions with NCCC. | 2020 |
| Actuator selection for over-actuated systems using the actuator effectiveness index | Mehdi Naderi, Ali Khaki Sedigh | This paper presents a new actuator selection methodology for over-actuated systems based on the actuator effectiveness index. In the proposed method, possible actuator candidates are quantitatively compared. The index is calculated for all candidates and is then used to select the appropriate actuator set based on their effectiveness. The desirable properties for the input selection method are discussed and several examples are presented to show that the results based on the proposed index are compatible with the field knowledge. Furthermore, the proposed actuator selection method is employed to set the actuators groups in the daisy chain type control allocation approaches.This leads to a better initial selection of the actuators and reduces the computational burden of the daisy chain type methods by considering the most effective actuators in the first group. | 2020 |
| Managed Pressure Drilling System State Estimation Using The Multiple Model Adaptive Estimation Approach | Amir Masoud Molaei, Amir Hossein Nikoofard, Ali Khaki-Sedigh, Lars Imsland | This paper studies state estimation in the presence of parametric uncertainties, with flow estimation in Managed Pressure Drilling as a case study. Downhole measurements in most MPD systems have low frequency due to communication with mud-pulse telemetry. Also, the drilling process has parametric uncertainties due to unknown friction and fluid density and unmodeled actuator dynamics and noise add to the system complexity. This paper proposes a bank of estimators for simultaneous estimation of the model states. A Multiple-Model Adaptive Estimation (MMAE) algorithm is presented that encompasses a bank of Kalman Filters (KFs). Each KF is designed to handle a specific segment of the parametric uncertainty. In this algorithm, a probabilistically weighted combination of the local state estimations is used. Simulation results reveal that the proposed method can satisfactory estimate the unmeasured states in … | 2020 |
| Static Output-Feedback Control Design for Discrete-Time Systems Using Reinforcement Learning | Amir Parviz Valadbeigi, Ali Khaki Sedigh, Frank L Lewis | This paper provides necessary and sufficient conditions for the existence of the static output-feedback (OPFB) solution to the H ∞ control problem for linear discrete-time systems. It is shown that the solution of the static OPFB H ∞ control is a Nash equilibrium point. Furthermore, a Q-learning algorithm is developed to find the H ∞ OPFB solution online using data measured along the system trajectories and without knowing the system matrices. This is achieved by solving a game algebraic Riccati equation online and using the measured data. A simulation example shows the effectiveness of the proposed method. | 2019 |
| A relay logic for total and partial loss of excitation protection in synchronous generators | Mahdi Rasoulpour, Turaj Amraee, Ali Khaki Sedigh | Loss of Excitation (LOE) is an important fault in synchronous generators which may cause the generator outage due to out-of-step(OS) conditions. Since the LOE protective relays act based on the impedance or admittance measurement at the generator terminals, they suffer from mal-operations caused by non-LOE phenomenon such as stable power swings. To preserve the security and dependability of the LOE protection, in this paper, some unique characteristics of LOE event are determined using the transient model of synchronous generators. In this paper, using the transient model of synchronous generators, some unique characteristics of LOE event are determined. Frequency decomposition and time domain analysis of active and reactive powers as well as the terminal voltages are used to define a suitable rule for LOE protection. A comprehensive list of full and partial LOE scenarios, power swing and other … | 2019 |
| Guaranteed feasible control allocation using model predictive control | Mehdi Naderi, Ali Khaki Sedigh, Tor Arne Johansen | This paper proposes a guaranteed feasible control allocation method based on the model predictive control. Feasible region is considered to guarantee the determination of the desired virtual control signal using the pseudo inverse methodology and is described as a set of constraints of an MPC problem. With linear models and the given constraints, feasible region defines a convex polyhedral in the virtual control space. In order to reduce the computational time, the polyhedral can be approximated by a few axis aligned hypercubes. Employing the MPC with rectangular constraints substantially reduces the computational complexity. In two dimensions, the feasible region can be approximated by a few rectangles of the maximum area using numerical geometry techniques which are considered as the constraints of the MPC problem. Also, an active MPC is defined as the controller to minimize the cost … | 2019 |
| A fault tolerant control scheme using the feasible constrained control allocation strategy | Mehdi Naderi, Tor Arne Johansen, Ali Khaki Sedigh | This paper investigates the necessity of feasibility considerations in a fault tolerant control system using the constrained control allocation methodology where both static and dynamic actuator constraints are considered. In the proposed feasible control al-location scheme, the constrained model predictive control (MPC) is employed as the main controller. This considers the admissible region of the control allocation problem as its constraints. Using the feasibility notion in the control allocation problem provides the main controller with information regarding the actuator′s status, which leads to closed loop system performance improvement. Several simulation examples under normal and faulty conditions are employed to illustrate the effectiveness of the proposed methodology. The main results clearly indicate that closed loop performance and stability characteristics can be significantly degraded by … | 2019 |
| Performance enhancement of unfalsified adaptive control strategy using fuzzy logic | Seyed Iman Habibi, Ali Khaki-Sedigh, Mojtaba Nouri Manzar | Unfalsified Adaptive Switching Supervisory Control (UASSC) is a performance-based data-driven methodology to control uncertain systems with the least possible plant assumptions. There are a set of pre-designed controllers in the controller bank, and the goal is to select the best controller at each time instance. The Multi-Model UASSC (MMUASSC) uses the UASSC concept, but it also benefits from a set of pre-specified models in the model bank. This paper introduces a method to improve the performance of the UASSC and MMUASSC by cost function manipulations and fuzzy logic concepts. To achieve this, fuzzy UASSC and fuzzy MMUASSC methods are introduced. In these methods, a time-varying coefficient, which is the output of a fuzzy system, is used along with the conventional cost functions. The input of this fuzzy system is chosen to properly reflect the performance of the corresponding controller in the … | 2019 |
| Frequency Domain Tuning of a Filtered Smith Predictor Based PIλ Controller and Its Application to Pressure Plant | Roohallah Azarmi, Mahsan Tavakoli-Kakhki, Alireza Fatehi, Ali Khaki Sedigh | This paper is devoted to proposing a simple method to tune the parameters of a fractional order PI (FOPI) controller. The studied control scheme is a fractional filtered Smith predictor (FFSP) structure, which can compensate for the inherently long dead time of the industrial processes. The proposed frequency domain scheme would be a practical approach to compensate the stable processes, which can be modeled by a fractional order counterpart of First Order Plus Dead Time (FOPDT) transfer function. Two fractional order filters are also used to improve the reference tracking and to enhance the robustness of the compensated system. The obtained results of practical implementation on a pressure plant and the comparison results are given to demonstrate the effectiveness of the proposed technique. | 2019 |
| Loss of field protection in synchronous generators based on data mining technique | M Rasoulpour, T Amraee, AK Sedigh | Loss of field (LOF) is a common fault in synchronous generators. Mason-Berdy scheme is the well-known and practical protective scheme to detect the LOF conditions. However, this impedance based method comes up with mal-operations under special situations such as under excitation operation, power swing phenomena, and partial LOF. In this paper, a new method based on data mining scheme is proposed considering the statistical correlation and zero-crossing function of electric variables as input training features. Moreover, new scenarios including special conditions such as condenser mode in both leading and lagging power factors are considered. In order to detect the LOF fault, the support vector machine (SVM) classifier is used. Results of the proposed method are comparable with conventional and improved Mason-Berdy schemes considering dependability, security and accuracy criteria. | 2019 |
| A novel method for chaos detection in heavy noisy environments based on distribution of energy | Farbod Setoudeh, Ali Khaki Sedigh, Mohsen Najafi | Detecting chaos in heavy-noise environments is an important issue in many fields of science and engineering. In this paper, first, a new criterion is proposed to recognize chaos from noise based on the distribution of energy. Then, a new method based on stationary wavelet transform (SWT) is presented for chaos detection that is recommended for data that contain more than 60% noise. This method is dependent on the distribution of signal’s energy in different frequency bands based on SWT for chaos detection which is robust to noisy environments. In this method, the effect of white noise and colored noise on the chaotic system is considered. As a case study, the proposed method is applied to detect chaos in two different oscillators based on memristor and memcapacitor. The simulation results are used to display the main points of the paper. | 2019 |
| Smith Predictor Based Sliding Mode Control for Torsional Vibration Control of Drillstring with Input Delay | Roya Sadeghi Mehr, Amirhossein Nikoofard, Ali Khaki Sedigh | This paper presents a smith predictor based sliding mode controller to eliminate torsional vibrations in oil well drillstrings. The drillstring model is considered as a torsional pendulum with four degrees-of-freedom. The control objective of the system is tracking desired angular velocity without stick-slip oscillations. The main purpose of this paper is to design a controller dealing with both input delay and uncertainty in the nonlinear bit-rock interaction appropriately. For robustness in the presence of parameter uncertainty in drillstring model a sliding mode controller is proposed. However, smith predictive control method is used to deal with input delay. Asymptotic stability of the system and reference angular velocity tracking is proved by the Lyapunov method. Simulation results confirm that, the designed controller is robust in the presence of parametric uncertainties while preventing torsional vibrations in the drillstring … | 2019 |
| Notice of Violation of IEEE Publication Principles: Fault Tolerant Control Scheme Using Adaptive Sliding Mode Control Allocation | Navid Abbasi, Ali Khaki Sedigh, Mehdi Naderi, Seyed Reza Jafari | Notice of Violation of IEEE Publication Principles “Fault Tolerant Control Scheme Using Adaptive Sliding Mode Control Allocation,” by N. Abbasi, A. K. Sedigh, M. Naderi and S. R. Jafari, in the Proceedings of the 6th International Conference on Control, Instrumentation and Automation (ICCIA), October 2019 After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE’s Publication Principles. This paper contains portions of text from the paper(s) cited below. A credit notice is used, but due to the absence of quotation marks or offset text, copied material is not clearly referenced or specifically identified. “Fault Tolerant Control for Over-actuated Systems: An Adaptive Correction Approach” by S. S. Tohidi, Y. Yildiz and I. Kolmanovsky, in the Proceedings of the American Control Conference (ACC), July 2016 … | 2019 |
| A Revised Mehrotra Predictor-Corrector algorithm for Model Predictive Control | Saman Cyrus, Ali Khaki Sedigh | Input constrained Model predictive control (MPC) includes an optimization problem which should iteratively be solved at each time-instance. The well-known drawback of model predictive control is the computational cost of the optimization problem. This results in restriction of the application of MPC to systems with slow dynamics, e.g., process control systems and small-scale problems. Therefore, implementing fast numerical optimization algorithms has been a point of interest. Interior-point methods are proved to be appropriate algorithms, from computational cost point-of-vie, to solve input-constrained MPC. In this paper first a modified version of Mehrotra’s predictor-corrector algorithm, a famous interior-point algorithm, is extended for quadratic programming problems and then is applied to the constrained model predictive control problems. Results show that as expected, the new algorithm is faster than Matlab solver’s algorithm. | 2019 |
| On the Stability of Nonlinear Minimum Variance Control for a Second-Order Volterra Series Model | L Mehri, MA Nekoui, A Khaki-Sedigh | In this paper, the stability of a closed-loop system with nonlinear minimum variance controller for a second order Volterra series model is studied. It is shown that the closed-loop system with secondorder Volterra series model and minimum variance control signal is a state-dependent switching system with an arbitrary switching signal. The necessary condition for asymptotic stability of this system is the stability of its all subsystems and is investigated using a linearization approach. Also, a sufficient closedloop stability condition with nonlinear minimum variance control is introduced. It is shown that if the sufficient stability condition is violated, it can be satisfied by using a generalized output and nonlinear generalized minimum variance control. | 2019 |
| Adaptive fuzzy dynamic surface control of nonlinear systems with input saturation and time-varying output constraints | L Edalati, A Khaki Sedigh, M Aliyari Shooredeli, A Moarefianpour | This paper deals with the design of adaptive fuzzy dynamic surface control for uncertain strict-feedback nonlinear systems with asymmetric time-varying output constraints in the presence of input saturation. To approximate the unknown nonlinear functions and overcome the problem of explosion of complexity, a Fuzzy logic system is combined with the dynamic surface control in the backstepping design technique. To ensure the output constraints satisfaction, an asymmetric time-varying Barrier Lyapunov Function (BLF) is used. Moreover, by applying the minimal learning parameter technique, the number of the online parameters update for each subsystem is reduced to 2. Hence, the semi-globally uniformly ultimately boundedness (SGUUB) of all the closed-loop signals with appropriate tracking error convergence is guaranteed. The effectiveness of the proposed control is demonstrated by two simulation examples. | 2018 |
| Applying a modified version of Lyapunov exponent for cancer diagnosis in biomedical images: the case of breast mammograms | Hamed Khodadadi, Ali Khaki-Sedigh, Mohammad Ataei, Mohammad Reza Jahed-Motlagh | Recently, there has been a great interest in the application of Lyapunov exponents for calculation of chaos levels in dynamical systems. Accordingly, this study aims at presenting two new methods for utilizing Lyapunov exponents to evaluate the spatiotemporal chaos in various images. Further, early detection of cancerous tumors could be obtained by measuring the chaotic indices in biomedical images. Unlike the available systems described by partial differential equations, the proposed method employs a number of interactive dynamic variables for image modeling. Since the Lyapunov exponents cannot be applied to such systems, the image model should be modified. The mean Lyapunov exponent is defined as a chaotic index for measuring the contour borders irregularities in images to detect benign or malignant tumors. Moreover, a two-dimensional mean Lyapunov exponent is incorporated to identify … | 2018 |
| Infinite horizon linear quadratic tracking problem: A discounted cost function approach | Soleiman Najafi Birgani, Bijan Moaveni, Ali Khaki‐Sedigh | The discounted cost function approach is one of the main approaches to the infinite time horizon problems in economics and market. This paper introduces a causal and optimal solution based on the discounted cost function approach for infinite horizon linear quadratic tracking problem with disturbance rejection and the problem of disturbance tracking by presenting the theoretical foundations. It is shown that the proposed method has the ability to solve the problems where the reference inputs and disturbance signals are not asymptotically stable. Two numerical examples, a grid connection of voltage source power electronic converter as a SISO system and a load frequency control of a 2‐area nonreheat thermal power system as a MIMO example, are presented to illustrate the effectiveness of the proposed method. | 2018 |
| Robustness improvement using the filtered Smith predictor based fractional integral-fractional derivative controllers: Application to a pressure plant | Roohallah Azarmi, Mahsan Tavakoli-Kakhki, Ramon Vilanova, Alireza Fatehi, Ali Khaki Sedigh | This article presents a simple frequency domain control technique to tune the parameters of a filtered Smith predictor based fractional integral-fractional derivative (FSP-FIFD) controller. The proposed method provides a practical approach to compensate stable First Order Plus Dead Time (FOPDT) transfer functions based on a filtered Smith predictor (FSP) control structure. In this control structure, an integer order predictor filter is used to improve the noise reduction of the control system. By benefiting from the proposed FSPFIFD controller, not only the phase margin and the gain crossover frequency of the control system are adjustable by tuning the free controller parameters, but also the robustness of the compensated system is enhanced. Finally, the designed FSPFIFD controller is implemented on a laboratory scale pressure plant and the obtained results are compared with those of applying a filtered Smith … | 2018 |
| Asymptotic tracking control of strict‐feedback non‐linear systems with output constraints in the presence of input saturation | Lida Edalati, Ali Khaki Sedigh, Mahdi Aliyari Shooredeli, Ali Moarefianpour | In this study, the asymptotic tracking control problem is addressed for known and unknown non‐linear systems in the strict‐feedback form with time‐varying output constraints, input saturation, and external disturbances. A barrier Lyapunov function is employed to prevent transgression of the output constraints. Neural networks are applied to approximate the unknown functions. To deal with the input saturation effects and/or neural networks reconstruction errors, the Nussbaum gain technique is suggested. The proposed approach guarantees the boundedness of all the closed‐loop signals, and for the first time, the asymptotic tracking property is achieved for the strict‐feedback non‐linear systems, while the actual output remains in the output constraints, despite input saturation and external disturbances. Two simulation examples have validated the effectiveness of the proposed results. | 2018 |
| A dynamic independent component analysis approach to fault detection with new statistics | M Teimoortashloo, A Khadi Sedigh | This paper presents a fault detection method based on Dynamic Independent Component Analysis (DICA) with new statistics. These new statistics are statistical moments and first characteristic function that surrogate the norm operator to calculate the fault detection statistics to determine the control limit of the independent components (ICs). The estimation of first characteristic function by its series is modified such that the effect of series remainder on estimation is reduced. The advantage of using first characteristic function and moments, over second characteristic function and cumulants, as fault detection statistics is also presented. It is shown that the proposed method can detect a class of faults that the former methods cannot; in particular faults with small amplitude ICs that have either different probability density function or identical probability density function of the ICs, but different low order moments of the ICs compared with the normal performance. Simulation results are used to show the effectiveness of the proposed method. | 2018 |
| Adaptive Tuning of Model Predictive Control Parameters Based on Analytical Results | Tahereh Gholaminejad, Ali Khaki-Sedigh, Peyman Bagheri | In dealing with model predictive controllers (MPC), controller tuning is a key designing step. Various tuning methods are proposed in the literature which can be categorized as heuristic, numerical and analytical methods. Among the available tuning methods, analytical approaches are more interesting and useful. This paper is based on a proposed analytical MPC tuning approach for plants which can be approximated by first-order plus dead-time models. The performance of such methods fails to deal with unknown or time-varying parameter plants. To overcome this problem, adaptive MPC tuning strategies are practical alternatives. The adaptive MPC tuning approach proposed in this paper is based on on-line identification and analytical tuning formulas. Simulation results are used to show the effectiveness of the proposed methodology. Also, a comparison of the proposed adaptive tuning method with a well-known online tuning method is presented briefly which shows the superiority of the proposed adaptive tuning method. | 2018 |
| Decentralized Model Reference Adaptive Control of Large Scale Interconnected Systems with Both State and Input Delays | SH Hashemipour, N Vasegh, A Khaki Sedigh | In this paper, the problem of decentralized Model Reference Adaptive Control (MRAC) for interconnected large scale systems associated with time varying delays in state and input is investigated. The upper bounds of the interconnection terms are considered to be unknown. Time varying delays in the nonlinear interconnection terms are bounded and non-negative continuous functions and their derivatives are not necessarily less than one. Moreover, a simple and practical method based on periodic characteristics of the reference model is established to predict the future states and input delay compensation. It is shown that the solution of uncertain large-scale time-delay interconnected system converges uniformly exponentially to inside of a desired small ball. Simulation results of a chemical reactor system and a numerical example illustrate effectiveness of the proposed methods. | 2018 |
| Applying Multiple Model Adaptive Control to Adjustment of Satellite Antenna Position with time varying input delay | Firouz Allahverdizadeh, Ali Khaki Sedigh, Jafar Rowshanian | In this paper, a new Multiple Model Adaptive Control (MMAC) is proposed to control of the satellite antenna position with time varying input delay. Selecting of adequate delay estimation method and weighting algorithm using delay estimation error are features of proposed controller. Input delay can be effect on the performance of the closed loop system and if delay time is unknown and time varying, the closed loop system will probably be unstable. At these cases, delay time must be identified to adopt control signal. It is assumed that upper bound of the delay time is known. Delay time is divided into several small bounds and then an adequate PI controller is designed for each bound to guarantee closed loop system performance and stability. In the on-line mode, delay time is identified by adequate estimation algorithm and the control signal is constructed by a weighted sum of the designed controllers output. Control signals weights are a function of the absolute error between the estimated and the average delay time in each bound. Performance of the proposed method and stability of closed-loop system is assessed using several simulations of the system. Simulation results confirm the effectiveness of the proposed algorithm with respect to conventional PI controller. | 2018 |
| Adaptive recurrent neural network with Lyapunov stability learning rules for robot dynamic terms identification | Pedram Agand, Mahdi Aliyari Shoorehdeli, Ali Khaki-Sedigh | In this paper, a recurrent neural network coupled with Kalman filter is proposed to identify dynamic terms of robotic manipulator. By cooperating some inherent characteristics of robot, this network has the capability to individually identify nonlinear terms using Weighted Augmentation Error (WAE). To present the infrastructure of architecture, an adaptive scheme based on the conventional Back Propagation (BP) is firstly driven using the Gradient Descent (GD) method. Additionally, a stable adaptive updating rule is extracted from the discrete time Lyapunov candidate as an approach for the general nonlinear system identification. Then, this approach is applied to the predefined network. To experimentally validate the computational efficiency and control applicability of the proposed method, Adaptive Neural Network Based Inverse Dynamic Control (ANN-Based-IDC) is employed on a laboratory-scaled twin-rotor CE … | 2017 |
| Ethics: An indispensable dimension in the university rankings | Ali Khaki Sedigh | University ranking systems attempt to provide an ordinal gauge to make an expert evaluation of the university’s performance for a general audience. University rankings have always had their pros and cons in the higher education community. Some seriously question the usefulness, accuracy, and lack of consensus in ranking systems and therefore multidimensional ranking systems have been proposed to overcome some shortcomings of the earlier systems. Although the present ranking results may rather be rough, they are the only available sources that illustrate the complex university performance in a tangible format. Their relative accuracy has turned the ranking systems into an essential feature of the academic lifecycle within the foreseeable future. The main concern however, is that the present ranking systems totally neglect the ethical issues involved in university performances. Ethics should be a … | 2017 |
| Input-constrained multi-model unfalsified switching control | Mojtaba Nouri Manzar, Giorgio Battistelli, Ali Khaki Sedigh | This note deals with the problem of controlling an uncertain multivariable plant in the presence of input saturation via switching among a finite family of controllers having a generalized anti-windup architecture. The problem is addressed within the multi-model unfalsified adaptive switching control framework. It is shown that proper definitions of fictitious references and test functionals allow to prove stability of the overall switching scheme, provided that at least one controller in the finite family is stabilizing. The satisfiability of this assumption is discussed and simulation results are reported. | 2017 |
| Nonlinear analysis of the contour boundary irregularity of skin lesion using Lyapunov exponent and KS entropy | Hamed Khodadadi, Ali Khaki Sedigh, Mohammad Ataei, Mohammad Reza Jahed Motlagh, Ali Hekmatnia | Measuring the contour boundary irregularities of skin lesion is an important factor in early detection of malignant melanoma. On the other hand, cancer is usually recognized as a chaotic growth of cells. It is generally assumed that boundary irregularity associated with biomedical images may be due to the chaotic behavior of its originated system. Thus, chaotic indices can serve as some criteria for classifying dermoscopy images. In this paper, a new approach is presented for extraction of Lyapunov exponent and Kolmogorov–Sinai entropy in the skin lesion images. This method is based on chaotic time series analysis. Converting the region of interest of skin lesion to a time series, reconstruction of system phase space, estimation of the Lyapunov exponents and calculation of Kolmogorov–Sinai entropy are the steps of the proposed approach. The combination of the largest Lyapunov exponent and … | 2017 |
| Multi-linear model set design based on the nonlinearity measure and H-gap metric | Davood Shaghaghi, Alireza Fatehi, Ali Khaki-Sedigh | This paper proposes a model bank selection method for a large class of nonlinear systems with wide operating ranges. In particular, nonlinearity measure and H-gap metric are used to provide an effective algorithm to design a model bank for the system. Then, the proposed model bank is accompanied with model predictive controllers to design a high performance advanced process controller. The advantage of this method is the reduction of excessive switch between models and also decrement of the computational complexity in the controller bank that can lead to performance improvement of the control system. The effectiveness of the method is verified by simulations as well as experimental studies on a pH neutralization laboratory apparatus which confirms the efficiency of the proposed algorithm. | 2017 |
| Decentralized model reference adaptive control for interconnected time delay systems with delay in state and compensation of long delay in input by nested prediction | Seyed Hamid Hashemipour, Nastaran Vasegh, Ali Khaki Sedigh | This paper investigates the problem of decentralized model reference adaptive control (MRAC) for a class of stable large scale interconnected systems. The interconnections are nonlinear with time varying delays which are bounded by polynomials with unknown gains. Also, it is assumed that both state and input delays are present. To overcome the input delay effect, a nested predictor based approach is adopted to predict the future states. The uniformly bounded stability of the closed loop system is proved by employing a suitable Lyapunov function. The effectiveness of the proposed approaches is illustrated by a numerical example. | 2017 |
| Decentralized MRAC for large-scale interconnected systems with state and input delays by integrators inclusion | Seyed Hamid Hashemipour, Nastaran Vasegh, Ali Khaki Sedigh | This paper investigates the problem of decentralized model reference adaptive control (MRAC) for a class of large-scale systems with time-varying delays in the interconnected terms and state and input delays. The upper bounds of interconnection terms with time-varying delays and external disturbances are assumed to be completely unknown. By integrators inclusion, a dynamic input delay compensator is established for input delay compensation and it is used as a practical method for state calculation x(t + R). Also, a method is presented for a class of decentralized feedback controllers, which can evolve the closed-loop system error uniformly bounded stable. As a numerical example, the proposed technique is applied to an unstable open-loop system to show the feasibility and effectiveness of the method. | 2017 |
| Robust H ∞ filtering for uncertain discrete-time descriptor systems | Sahereh Beidaghi, Ali Akbar Jalali, Ali Khaki Sedigh, Bijan Moaveni | This paper considers the robust H ∞ filtering problem for uncertain discrete-time descriptor systems. A class of uncertain systems with norm-bounded uncertainties is considered. The necessary and sufficient condition for solvability of the robust full-order H ∞ filtering is introduced which is generally less conservative than those existing sufficient conditions only. Explicit expressions of these filters are given. In addition to the full-order filtering problem, the robust reduced-order H ∞ filtering is also addressed by using slack variables technique in new sufficient conditions. The parameters of reduced-order filters are directly extracted from the solvability conditions. All the above conditions are convex and are expressed in term of linear matrix inequalities (LMIs) by using the original system matrices. The results generalize the previously developed H … | 2017 |
| Direct adaptive model predictive control tuning based on the first‐order plus dead time models | Tahereh Gholaminejad, Ali Khaki‐Sedigh, Peyman Bagheri | A direct adaptive tuning strategy is proposed for model predictive controllers. Parameter tuning is essential for a satisfactory control performance. Various tuning methods are proposed in the literature which can be categorised as heuristic, numerical and analytical methods. The proposed tuning methodology is based on an analytical model predictive control tuning approach for plants described by first‐order plus dead time models. For a fixed tuning scheme, the tuning performance deteriorates in dealing with unknown or time varying plants. To overcome this problem, an adaptive tuning strategy is utilised. It is suggested to employ a discrete‐time model reference adaptive control with recursive least squares estimations for controller tuning. The proposed method is also extended to multivariable systems. The stability and convergence of the proposed strategy is proved using the Lyapunov approach. Finally … | 2017 |
| Self‐falsification in multimodel unfalsified adaptive switching control | Mojtaba Nouri Manzar, Ali Khaki‐Sedigh | This paper addresses a multimodel unfalsified adaptive switching control with finite fixed time window cost function by utilizing a self‐falsification strategy. A closed‐loop stability proof is provided, and it is shown that the forgetting factor employed with finite fixed windowed cost function improves the closed‐loop performance. Furthermore, it is shown that the unfalsified adaptive control with nonmonotone cost function is unable to select the appropriate controller, and a new reset strategy is proposed to resolve this problem. The γ sequence monotonicity in the linear increasing cost‐level algorithm causes a performance deterioration, and a γ sequence reset is introduced for performance enhancement. Effectiveness of the proposed method is investigated for a nonlinear pH neutralization process and the 2‐cart benchmark example. | 2017 |
| Model-free subspace approach to NLQG controller design using bilinear model | Saman Rahmani, Hamid Khaloozadeh, Ali Khaki-Sedigh | In this paper, Linear Quadratic Gaussian (LQG) controller extended to a class of nonlinear systems based on subspace matrices using bilinear model. LQG controller design based on subspace matrices provides directly from system input output data. Therefore it is more useful for systems that their models are not available. Since the most practical systems are nonlinear, LQG controller design based on linear subspace model is reflected to a weak control performance or even instability. To overcome this problem, LQG controller design based on bilinear subspace model is presented. Simulation results and comparison studies are provided to show the effectiveness of proposed method. | 2017 |
| New H 2 filtering for descriptor systems: Singular and normal filters | Sahereh Beidaghi, Ali Akbar Jalali, Ali Khaki Sedigh | This paper considers the H 2 filtering problem for continuous-time descriptor systems by revisiting the H 2 performance and introducing the new formulation. Differing from previous results, recent note provides solvability conditions of the H 2 filtering problem with both the singular and the normal filters. The results are introduced as necessary and sufficient conditions for the singular filters and as sufficient conditions for the normal filters. These conditions are extracted without decomposing the original system matrices and are expressed in terms of strict linear matrix inequalities (LMIs). A numerical example with simulation results is given to illustrate the effectiveness of the proposed methods. | 2017 |
| Fault tolerant control design using adaptive control allocation based on the pseudo inverse along the null space | Seyed Shahabaldin Tohidi, A Khaki Sedigh, David Buzorgnia | Fault‐tolerant control systems are vital in many industrial systems. Actuator redundancy is employed in advanced control strategies to increase system maneuverability, flexibility, safety, and fault tolerability. Management of control signals among redundant actuators is the task of control allocation algorithms. Simplicity, accuracy and low computational cost are key issues in control allocation implementations. In this paper, an adaptive control allocation method based on the pseudo inverse along the null space of the control matrix (PAN) is introduced in order to adaptively tolerate actuator faults. The proposed method solves the control allocation problem with an exact solution and optimized l∞ norm of the control signal. This method also handles input limitations and is computationally efficient. Simulation results are used to show the effectiveness of the proposed method. Copyright © 2016 John Wiley & Sons, Ltd. | 2016 |
| Robust fractional order PI controller tuning based on Bode’s ideal transfer function | Roohallah Azarmi, Mahsan Tavakoli-Kakhki, Ali Khaki Sedigh, Alireza Fatehi | This paper presents a simple analytical method for tuning the parameters of fractional order PI (FOPI) controllers based on Bode’s ideal transfer function. The proposed technique is applicable to stable plants describable by a fractional order counterpart of first order transfer function without time delay. Tuning rules are given in order to improve the robustness of the compensated system in the presence of gain uncertainty in the plant model. Finally, the designed FOPI controller is implemented on a laboratory scale twin rotor helicopter and comparison results are provided to show the effectiveness of the proposed tuning rules. | 2016 |
| Control performance assessment based on sensor fusion techniques | S Afshar Khamseh, A Khaki Sedigh, B Moshiri, A Fatehi | Control performance assessment techniques are widely studied and many performance assessment indices have been proposed. In this paper, a control performance assessment technique for multi-loop control systems is presented based on the decision fusion strategy. Since decisions based on individual indices can lead to erroneous results, decision fusion of different indices can improve the assessment accuracy, especially in multi-loop control systems in the presence of loop interactions. Performance assessment indices are individually evaluated and decisions based on these indices are fused. The results of simulation and practical implementation on series cascade control structures illustrate the effectiveness of the proposed algorithm. | 2016 |
| Immersion and invariance adaptive velocity observer for a class of Euler–Lagrange mechanical systems | Mehdi Tavan, Ali Khaki-Sedigh, Mohammad-Reza Arvan, Ahmad-Reza Vali | This paper addresses the problem of velocity estimation for a class of uncertain mechanical systems. Using advantages of immersion and invariance technique with input–output filtered transformation, a proper immersion and dynamical auxiliary filter have been constructed in the designed estimator. Uniform global asymptotic convergence of the velocity estimator has been proved for the system with parametric uncertainties. In the presence of perturbations on the input and output, the performance analysis of the estimator has been theoretically investigated and illustrated by simulation results. | 2016 |
| Adaptive tuning of model predictive control based on analytical results | Tahereh Gholaminejad, Ali Khaki-Sedigh, Peyman Bagheri | In dealing with model predictive controllers (MPC), controller tuning is a key design step. Among the available tuning methods, analytical approaches are more interesting and useful. This paper is based on a recently proposed analytical MPC tuning approach based on low order models. The performance of such methods deteriorates in dealing with unknown or time varying parameter plants. To overcome this problem, adaptive MPC tuning strategies are practical alternatives. The adaptive MPC tuning approach proposed in this paper is based on on-line identification and analytical tuning formulas. Simulation results are used to show the effectiveness of the proposed methodology. | 2016 |
| Particle filters for non-gaussian hunt-crossley model of environment in bilateral teleoperation | Pedram Agand, Hamid D Taghirad, Ali Khaki-Sedigh | Optimal solution for nonlinear identification problem in the presence of non-Gaussian distribution measurement and process noises is generally not analytically tractable. Particle filters, known as sequential Monte Carlo method (SMC), is a suboptimal solution of recursive Bayesian approach which can provide robust unbiased estimation of nonlinear non-Gaussian problem with desire precision. On the other hand, Hunt-Crossley is a widespread nonlinear model for modeling telesurgeries environment. Hence, in this paper, particle filter is proposed to capture most of the nonlinearities in telesergerie environment model. An online Bayesian framework with conventional Monte Carlo method is employed to filter and predict position and force signals of environment at slave side respectively to achieve transparent and stable bilateral teleoperation simultaneously. Simulation results illustrate effectiveness of the algorithm … | 2016 |
| SDRE control of non-affine systems | Kiumars Azimi Roudkenary, Hamid Khaloozadeh, Ali Khaki Sedigh | In this paper, we present a new method for obtaining closed-form SDC matrices for synthesis of SDRE controller for non-affine nonlinear systems. Furthermore, we design SDRE controller with OCU method for proposed SDC form. Simulation results shows that proposed method for designing SDRE controller yields good tracking performance and smoothness of control signals. Robustness of the designed SDRE controller will be illustrated to a class of external disturbances. | 2016 |
| Low-complexity control of hybrid systems using approximate multi-parametric MILP | Jalal Habibi, Behzad Moshiri, Ali Khaki Sedigh, Manfred Morari | Control of hybrid systems faces computational complexity as a main challenging problem. To reduce the computational burden, multi-parametric programming has been proposed to obtain the explicit solution of the optimal control problems for some classes of hybrid systems. This strategy provides the solution as a function of the state variables which can be obtained in an off-line fashion. A shortcoming of this technique is that the complexity of the explicit solution is again prohibitive for large problems. The main contribution of this paper is the introduction of an approximation algorithm for solving a general class of multi-parametric mixed-integer linear programming (mp-MILP) problems. The algorithm selects those binary sequences that make significant improvement in the objective function, if considered. It is shown that significant reduction in computational complexity can be achieved by introducing adjustable … | 2016 |
| Constrained dynamic control allocation in the presence of singularity and infeasible solutions | David Buzorgnia, Ali Khaki-Sedigh | Reliable controllers with high flexibility and performance are necessary for the control of intricate, advanced, and expensive systems such as aircraft, marine vessels, automotive vehicles, and satellites. Meanwhile, control allocation has an important role in the control system design strategies of such complex plants. Although there are many proposed control allocation methodologies, few papers deal with the problems of infeasible solutions or system matrix singularity. In this paper, a pseudo inverse based method is employed and modified by the null space, least squares, and singular value decomposition concepts to handle such situations. The proposed method could successfully give an appropriate solution in both the feasible and infeasible sections in the presence of singularity. The analytical approach guarantees the solution with pre-defined computational burden which is a noticeable privilege than the linear and quadratic optimization methods. Furthermore, the algorithm complexity is proportionately grown with the feasible, infeasible, and singularity conditions. Simulation results are used to show the effectiveness of the proposed methodology. | 2016 |
| Analytical design of fractional order PID controllers based on the fractional set-point weighted structure: Case study in twin rotor helicopter | Roohallah Azarmi, Mahsan Tavakoli-Kakhki, Ali Khaki Sedigh, Alireza Fatehi | In this paper, an analytical method for tuning the parameters of the set-point weighted fractional order PID (SWFOPID) controller is proposed. The studied control scheme is the filtered fractional set-point weighted (FFSW) structure. Also to achieve a desired closed-loop performance, a fractional order pre-filter is employed. The proposed method is applicable to stable plants describable by a simple three-parameter fractional order model. Such a model can be considered as the fractional order counterpart of a first order transfer function without time delay. Finally, the proposed method is implemented on a laboratory scale CE 150 helicopter platform and the results are compared with those of applying a filtered fractional order PI (FFOPI) controller in a similar structure. The practical results show the effectiveness of the proposed method. | 2015 |
| Robust tuning of dynamic matrix controllers for first order plus dead time models | Peyman Bagheri, Ali Khaki Sedigh | Dynamic Matrix Control is a widely used Model Predictive Controller in industrial processes. The successful implementation of Dynamic Matrix Control in practical applications requires appropriate tuning of the controller parameters. Three different cases are considered. In the first case, a tuning formula is developed that ensures the nominal closed loop desired performance. However, this formula may fail in the presence of plant uncertainty. Therefore a lower bound for the tuning parameter is derived to secure the robust stability of the uncertain first order plus dead time plant. Finally, a tuning boundary is derived which gives the lower and upper permissible bounds for the tuning parameter that guarantee the robust performance of the uncertain first order plus dead time plant. The tuning procedure is based on the application of Analysis of Variance, curve fitting and nonlinear regression analysis. The derived results … | 2015 |
| Design and implementation of Smith predictor based fractional order PID controller on MIMO flow-level plant | Roohallah Azarmi, Ali Khaki Sedigh, Mahsan Tavakoli-Kakhki, Alireza Fatehi | The main point of this paper is to present an iterative optimization strategy for tuning the parameters of Smith predictor based fractional order PID (SPFOPID) controller. The control scheme considered in this paper is the standard Smith predictor structure. Also, the internal model is considered to be a First Order Plus Dead Time (FOPDT) transfer function. Finally, the proposed method is implemented on a multi input-multi output (MIMO) flow-level plant and the obtained results are compared with the results of applying Smith predictor based PID controller (SPPID) in the similar structure. | 2015 |
| Closed form tuning equations for model predictive control of first-order plus fractional dead time models | Peyman Bagheri, Ali Khaki-Sedigh | Many industrial processes can be effectively described with first-order plus fractional dead time models. In the case of plants with a large dead time relative to the time constant, approximations in discretizing the time delay can adversely affect the performance and if the sample time is enforced by system requirements, the fractional nature of the delay should be considered. In this paper, an analytical approach to model predictive control tuning for stable and unstable first-order plus dead time models with fractional delay is presented. The existing tuning methods are based on trial and error or numerical optimization approaches and the available closed form equations are limited to plants with integer delays. In this paper, an analytical approach is adopted and the issues of closed loop stability and achievable performance are addressed. Finally, simulation results are used to show the effectiveness of the … | 2015 |
| An indirect adaptive predictive control for the pitch channel autopilot of a flight system | Karim Salahshoor, Ali Khaki-Sedigh, Pouria Sarhadi | In this paper a novel method for adaptive predictive control of a launch vehicle is presented. Nonlinear dynamics of these systems cause challenging problems in controller design. Linearizing the system in diverse operating points and designing appropriate controllers for these systems is an interesting idea in industry. The outcome is a linear time varying (LTV) system. Dealing with time varying dynamics is a challenging issue in control theory. Adaptive control approach presents a well-established methodology to address the subject of flight control systems. This paper proposes an indirect adaptive predictive idea to control the pitch channel dynamics of a launch vehicle. For this purpose, a robust estimator and a robustly-tuned generalized predictive controller are incorporated to present a robust adaptive scheme. The proposed technique is applied to pitch channel model of Vanguard missile. A set of test … | 2015 |
| Attitude flight control system design of UAV using LQG\LTR multivariable control with noise and disturbance | Ehsan Barzanooni, Karim Salahshoor, Ali Khaki-Sedigh | Unmanned Aerial Vehicles (UAVs) pose a multi-input and multi-output (MIMO) dynamic structure, making their simultaneous guidance and control too complicated to be maintained via conventional scalar controllers. In this paper, a multivariable optimal controller is introduced based upon LQG\LTR design approach to effectively control the UAV attitude in the presence of noise and disturbance. The regulator design problem is solved by generating an optimal state estimate using a Kalman filter. A loop transfer recovery (LTR) procedure is developed to allow good recovery of the full state feedback properties, enhancing stability and performance robustness. This scheme facilitates proper integration of system’s gain at different frequencies in order to provide optimal bandwidth and yet weakening the noise effects. The corresponding rate of return gains is set in frequency-domain to achieve robust performance … | 2015 |
| Tuning of generalized predictive controllers for first order plus dead time models based on anova | Zahed Ebrahimi, Peyman Bagheri, Ali Khaki-Sedigh | Successful implementation of predictive controller requires an appropriate tuning of its parameters. Closed form tuning equations are practically rewarding as they can be easily implemented with relatively low computational costs. In this paper, a tuning strategy for the generalized predictive control of single input-single output and multi input-multi output plants is presented. First order plus dead time model of the plant is considered and analysis of variance and nonlinear fitting is employed to derive tuning equations. Finally, simulation results are used to verify the efficiency of the proposed tuning strategy. | 2015 |
| Non-linear generalised minimum variance control state space design for a second-order Volterra series model | Mohsen Maboodi, Eduardo F Camacho, Ali Khaki-Sedigh | This paper presents a non-linear generalised minimum variance (NGMV) controller for a second-order Volterra series model with a general linear additive disturbance. The Volterra series models provide a natural extension of a linear convolution model with the nonlinearity considered in an additive term. The design procedure is entirely carried out in the state space framework, which facilitates the application of other analysis and design methods in this framework. First, the non-linear minimum variance (NMV) controller is introduced and then by changing the cost function, NGMV controller is defined as an extended version of the linear cases. The cost function is used in the simplest form and can be easily extended to the general case. Simulation results show the effectiveness of the proposed non-linear method. | 2015 |
| Control performance assessment for a class of nonlinear systems using second-order Volterra series models based on nonlinear generalised minimum variance control | Mohsen Maboodi, Ali Khaki-Sedigh, Eduardo F Camacho | In this paper, control performance assessment for a class of nonlinear systems modelled by autoregressive second-order Volterra series with a general linear additive disturbance is presented. The proposed approach employs the nonlinear generalised minimum variance (NGMV) controller concept. The Volterra series models provide a natural extension of a linear convolution model with the nonlinearity considered in an additive term. The polynomial operator form is used throughout this paper for the description of the system input–output model. The closed form formulation of NGMV controller for autoregressive second-order Volterra series is presented in a polynomial form then a control assessment criterion based on the NGMV control is given. Simulation results and comparison studies are used to show the effectiveness of the proposed approach for a class of nonlinear systems. | 2015 |
| Control of multichaotic systems using the extended OGY method | Ensieh Nobakhti, Ali Khaki-Sedigh, Nastaran Vasegh | This paper considers the problem of controlling coupled chaotic maps. Coupled chaotic maps or multichaotic subsystems are complex dynamical systems that consist of several chaotic sub-systems with interactions. The OGY methodology is extended to deal with the control of such systems. It is shown that the decentralized control design scheme in which the individual controllers share no information is not generally able to control multichaotic systems. Simulation results are used to support the main conclusions of the paper. | 2015 |
| X–Y pedestal: partial quasi-linearization and cascade-based global output feedback tracking control | Mehdi Tavan, Ali Khaki-Sedigh, Mohammad Reza Arvan, Ahmad Reza Vali | This paper addresses the problem of output (angular position) feedback tracking control of two-degree-of-freedom X–Y pedestal systems. Both the velocity observer and the controller are based on a partial quasi-linearized model for the X–Y pedestal system. The two-dimensional velocity observer is uniformly globally exponentially convergent and does not require a priori upper-bound knowledge of the velocity magnitude. An important feature of the proposed observer is that it constructs a uniform global stable output feedback tracking controller with any domain of initial tracking errors and initial estimation errors. The proof of the main results is based on the well-established theorems for cascaded nonlinear time-varying systems. Due to uniform asymptotic stability of the observer and the output feedback controller, numerical simulations show their robust performance in the face of bounded additive … | 2015 |
| A novel alignment repulsion algorithm for flocking of multi-agent systems based on the number of neighbours per agent | R Kahani, AK Sedigh, M Gh Mahjani | In this paper, an energy-based control methodology is proposed to satisfy the Reynolds three rules in a flock of multiple agents. First, a control law is provided that is directly derived from the passivity theorem. In the next step, the Number of Neighbours Alignment/Repulsion algorithm is introduced for a flock of agents which loses the cohesion ability and uniformly joint connectivity condition. With this method, each agent tries to follow the agents which escape its neighbourhood by considering the velocity of escape time and number of neighbours. It is mathematically proved that the motion of multiple agents converges to a rigid and uncrowded flock if the group is jointly connected just for an instant. Moreover, the conditions for collision avoidance are guaranteed during the entire process. Finally, simulation results are presented to show the effectiveness of the proposed methodology. | 2015 |
| A modified independent component analysis-based fault detection method in plant-wide systems | Mazdak Teimoortashloo, Ali Khaki Sedigh | This paper presents a modified Independent Component Analysis (ICA)-based Fault Detection Method (FDM). The proposed FDM constructs a set of matrices, revealingthe trend of the variable samples and execute ICA algorithm for each set of matrices in contrast to the FDM based on dynamic ICA (DICA) which constructs the high dimensional augmented matrix. This paper shows that the proposed FDM decreases the matrix dimensions and as a result compensates for some disadvantages of using the high dimensional matrix discussed in previous articles. Furthermore, other advantages of the proposed FDM are the decreases in the running time, computational cost of the algorithm and the orthogonalization estimation errors. Moreover, the proposed method improves the detectability for a class of faults compared to DICA-based FDM. This class of fault occurs when two or more consecutive samples of fault source signal have opposite signs and cancel out each other. Simulation results are provided to show the effectiveness of the proposed methodology. | 2015 |
| Multi-model unfalsified predictive supervisory control | MANZAR MOJTABA NOURI, SEDIGH ALI KHAKI | Unfalsified Adaptive Control (UAC) is a recently proposed robust adaptive control strategy. In this paper, the UAC principles and algorithms are reviewed and Multi-Model UAC is followed as an intermediate between UAC and multiple model control. Different approaches in UAC and MMUAC are studied. Also, Multi-Model Unfalsified Generalized Predictive control (MMUGPC) is proposed, which is a new control design strategy in the UAC framework. For an uncertain system, by utilizing several generalized predictive controllers and discrete switching between them with unfalsified control, a new structure is proposed and appropriate equations are derived. Simulation results show the effectiveness of proposed Multi-Model Unfalsified Generalized Predictive control. | 2015 |
| Latency Compensation in Multi Chaotic Systems Using the Extended OGY Control Method | Ensieh Nobakhti, Ali Khaki Sedigh | The problem discussed in this paper is the effect of latency time on the OGY chaos control methodology in multi chaotic systems. The Smith predictor, rhythmic and memory strategies are embedded in the OGY chaos control method to encounter loop latency. A comparison study is provided and the advantages of the Smith predictor approach are clearly evident from the closed loop responses. The complex plants considered are coupled chaotic maps controlled by the extended OGY scheme. Simulation results are used to show the effectiveness of the applied Smith predictor scheme structure in multi chaotic systems. | 2015 |
| شیپ یتراظن لزتنک نیب لاطبا ذپان هناگدنچ لدم زی | Mojtaba Nouri Manzar, Ali Khaki Sedigh | Unfalsified Adaptive Control (UAC) is a recently proposed robust adaptive control strategy. In this paper, the UAC principles and algorithms are reviewed and Multi-Model UAC is followed as an intermediate between UAC and multiple model control. Different approaches in UAC and MMUAC are studied. Also, Multi-Model Unfalsified Generalized Predictive control (MMUGPC) is proposed, which is a new control design strategy in the UAC framework. For an uncertain system, by utilizing several generalized predictive controllers and discrete switching between them with unfalsified control, a new structure is proposed and appropriate equations are derived. Simulation results show the effectiveness of proposed Multi-Model Unfalsified Generalized Predictive control. | 2015 |
| An analytical tuning approach to multivariable model predictive controllers | Peyman Bagheri, Ali Khaki-Sedigh | Multivariable model predictive control is a widely used advanced process control methodology, where handling delays and constraints are its key features. However, successful implementation of model predictive control requires an appropriate tuning of the controller parameters. This paper proposes an analytical tuning approach to multivariable model predictive controllers. The considered multivariable plants are square and consist of first-order plus dead time transfer functions. Most of the existing model predictive control tuning methods are based on trial and error or numerical approaches. In the case of no active constraints, closed loop transfer function matrices are derived and decoupling conditions are addressed. For control horizon of one, analytical tuning equations and achievable performances are obtained. Finally, simulation results are used to verify the effectiveness of the proposed tuning strategy. | 2014 |
| Robust second order sliding mode control for a quadrotor considering motor dynamics | Nader Jamali Soufi Amlashi, Mohammad Rezaei, Hossein Bolandi, Ali Khaki Sedigh | In this paper, a robust second order sliding mode control (SMC) for controlling a quadrotor with uncertain parameters presented based on high order sliding mode control (HOSMC). A controller based on the HOSMC technique is designed for trajectory tracking of a quadrotor helicopter with considering motor dynamics. The main subsystems of quadrotor (ie position and attitude) stabilized using HOSMC method. The performance and effectiveness of the proposed controller are tested in a simulation study taking into account external disturbances with consider to motor dynamics. Simulation results show that the proposed controller eliminates the disturbance effect on the position and attitude subsystems efficiency that can be used in real time applications. | 2014 |
| /Predictive output control of a three-axis gyrostabilized platform | Mahdy Rezaei Darestani, Amir Ali Nikkhah, Ali Khaki Sedigh | In the presence of plant uncertainties, utilizing an appropriate controller for a smooth output tracking and elimination of high-frequency disturbances, especially in accurate systems is very important. In this paper, a controller is proposed based on the robust and optimal theory to achieve a combination of such characteristics in the face of model parameter variations and unknown disturbances. The proposed controller has been simulated on a three-axis gyro-stabilized MIMO platform and comparison results with a NLPID controller simulation are provided. | 2014 |
| Control of cardiac arrhythmia by nonlinear spatiotemporal delayed feedback | Forough Rezaei Boroujeni, Nastaran Vasegh, Ali Khaki Sedigh | The dynamic feedback control of the cardiac pacing interval has been widely used to suppress alternans. In this paper, temporally and spatially suppressing the alternans for cardiac tissue consisting of a one-dimensional chain of cardiac units is investigated. The model employed is a nonlinear partial difference equation. The model’s fixed points and their stability conditions are determined, and bifurcations and chaos phenomenon have been studied by numerical simulations. The main objective of this paper is to stabilize the unstable fixed point of the model. The proposed approach is nonlinear spatiotemporal delayed feedback, and the appropriate interval for controller feedback gain is calculated using the linear stability analysis. It is proven that the proposed approach is robust with respect to all bifurcation parameter variations. Also, set point tracking is achieved by employing delayed feedback with an integrator … | 2014 |
| Analysis of a chaotic memristor based oscillator | F Setoudeh, A Khaki Sedigh, M Dousti | A chaotic oscillator based on the memristor is analyzed from a chaos theory viewpoint. Sensitivity to initial conditions is studied by considering a nonlinear model of the system, and also a new chaos analysis methodology based on the energy distribution is presented using the Discrete Wavelet Transform (DWT). Then, using Advance Design System (ADS) software, implementation of chaotic oscillator based on the memristor is considered. Simulation results are provided to show the main points of the paper. | 2014 |
| Direct and indirect output feedback design for TORA system | Mehdi Tavan, Ali Khaki-Sedigh, Sara Pakzad | This paper addresses the problem of stabilizing a TORA system without velocity measurement. For this purpose, two classes of output feedback designs, direct and indirect, are employed to design a nonlinear observer for estimating an unavailable variable (velocity variable). Moreover, the theory of cascaded time-varying systems has been used to improve the indirect output feedback controller and to enable the independent tuning of the observer and the controller. The results of Lyapunov stability analysis show globally asymptotic stability of the system in closed loop using the output feedback controllers designed in this paper. | 2014 |
| Application of augmented UD identification with selective forgetting in an adaptive control loop | Pouria Sarhadi, Karim Salahshoor, Ali Khaki-Sedigh | Robustness of parameter estimator plays a vital role in adaptive controllers. A modified identification algorithm is proposed based on the augmented UD identification (AUDI) primary version. Augmented UD identification with selective forgetting (AUDSF) method is derived as a robust derivation of AUDI to be integrated with input-output data filtering, relative dead zone, and data normalisation features. AUDSF is incorporated by generalised predictive controller (GPC) strategy to produce an applicable adaptive control method. The comparative performances of the developed approach have been explored on two-mass spring challenging benchmark problem, which demonstrates its excellent behaviour under conducted parameter and disturbance uncertainty scenarios. | 2014 |
| Review of model predictive control tuning methods and modern tuning solutions | Ali Khaki Sedigh, Peyman Bagheri | Model Predictive Controllers (MPC) are effective control strategies widely used in the industry. The desirable MPC performance requires appropriate tuning of the controller parameters. However, the MPC tuning parameters are related to the closed loop characteristics in a complex and nonlinear manner, so the tuning procedure is an intricate problem, which has received much attention in recent decades. In this paper, the effects of each tuning parameter on the closed loop behavior are studied. Then, the issue of MPC tuning problem is considered and a review of the available tuning methods are provided. Modern tuning strategies are also considered. The emphasis of this paper is on theoretical tuning strategies which lead to closed form tuning equations that can be used in closed loop analysis. Finally, a simulation study is employed to have a comparative study on some closed form tuning equations and the advantages and disadvantages of each method is clarified. | 2014 |
| Switching-tuning adaptive multiple model predictive control | Ali Shamsaddinlou, Alireza Fatehi, Ali Khaki Sedigh | In this paper, an adaptive multiple model predictive controller (AMMPC) based on multiple model switching and tuning strategy and dynamic matrix control (DMC) system is presented to construct switching-tuning adaptive multiple model predictive controller (STAMMPC). Disadvantages of non adaptive multiple model predictive control (MMPC) in regulation and disturbance rejection are discussed and new robust adaptive supervisors to improve the decision making procedures are developed. Experimental results on pH neutralization process show that the proposed decentralized control strategy using STAMMPC algorithm has desirable performance and robustness characteristics and is superior to the other MMPC algorithms, especially in the case of the participation with suggested new adaptive disturbance rejection supervisor. | 2014 |
| Adaptive Simplified Model Predictive Control with Tuning Considerations | AS Ashtari, SEDIGH A KHAKI | Model predictive controller is widely used in industrial plants. Uncertainty is one of the critical issues in real systems. In this paper, the direct adaptive Simplified Model Predictive Control (SMPC) is proposed for unknown or time varying plants with uncertainties. By estimating the plant step response in each sample, the controller is designed and the controller coefficients are directly calculated. The proposed method is validated via simulations for both slow and fast time varying systems. Simulation results indicate the controller ability for tracking references in the presence of plant’s time varying parameters. In addition, an analytical tuning method for adjusting prediction horizon is proposed based on optimization of the objective function. It leads to a simple formula including the model parameters, and an indirect adaptive controller can be designed based on the analytical formula. Simulation results indicate a better performance for the tuned controller. Finally, experimental tests are performed to show the effectiveness of the proposed methodologies. | 2014 |
| A comparison of alternative strategies for optimal utilisation of tyre friction forces aimed at vehicle lateral-plane motion control | Javad Ahmadi, Ali Khaki-Sedigh | In this paper, three strategies are analysed and compared for optimal determination of tyre friction forces used for vehicle lateral-plane motion control. The valueability of this determination depends on the feasibility of the solution of a real-time optimisation problem. In strategy (III), the optimisation problem is relaxed from the equality constraints (enforced in strategies (I) and (II)) posed owing to the stabilisation and tracking objectives of the closed loop and instead these objectives are included in the cost function of the optimisation problem. In this way, the problem of the existence of feasible solution encountered in strategy (II) is remedied without infringing the saturation restrictions imposed by the limited physical capability of the tyres and actuators in developing tyre friction forces, which was overlooked in strategy (I). Detailed simulation studies show convincing performance that can be achieved with strategy (III) in … | 2014 |
| Experimental implementation of an integrated robust optimal control on a 3axis gyro-stabilized platform | AA Nikkhah, M Rezaei Darestani, A Khaki Sedigh | An improved performance integral Combined Predictive Control, in the presence of disturbances and uncertainties is implemented on a 3 axis gyrostabilized platform in this paper. The 3 axis gyrostabilized platform is set up in navigation laboratory of KN Toosi University of Technology for stabilization of a video camera. A model predictive controller (MPC) is used in the outer control loop for reaching a smooth tracking, and an integrated 2/∞ control to high frequency disturbance rejection in the inner control loop. Results of experimental set up of gyro stabilized platform shows the same reaction of two controllers as they uses integral derivative of control inputs. | 2014 |
| Analytical approach to tuning of model predictive control for first‐order plus dead time models | Peyman Bagheri, Ali Khaki Sedigh | Model predictive control (MPC) is an effective control strategy in the presence of system constraints. The successful implementation of MPC in practical applications requires appropriate tuning of the controller parameters. An analytical tuning strategy for MPC of first‐order plus dead time (FOPDT) systems is presented when the constraints are inactive. The available tuning methods are generally based on the user’s experience and experimental results. Some tuning methods lead to a complex optimisation problem that provides numerical results for the controller parameters. On the other hand, many industrial plants can be effectively described by FOPDT models, and this model is therefore used to derive analytical results for the MPC tuning in a pole placement framework. Then, the issues of closed‐loop stability and possible achievable performance are addressed. In the case of no active constraints, it is shown that … | 2013 |
| Short-term traffic flow forecasting: parametric and nonparametric approaches via emotional temporal difference learning | Javad Abdi, Behzad Moshiri, Baher Abdulhai, Ali Khaki Sedigh | Information signal from real case and natural complex dynamical systems such as traffic flow are usually specified by irregular motions. Chaotic nonlinear dynamics approach is now the most powerful tool for scientists to deal with complexities in real cases, and neural networks and neuro-fuzzy models are widely used for their capabilities in nonlinear modeling of chaotic systems more than the traditional methods. As mentioned, the traffic flow conditions caused the forecasting values of traffic flow to lack robustness and accuracy. In this paper, the traffic flow forecasting is analyzed with emotional concepts and multi-agent systems (MASs) points of view as a new method in this field. The findings enabled the researchers to develop a newly object-oriented method of forecasting traffic flow. Its architecture is based on a temporal difference (TD) Q-learning with a neuro-fuzzy structure, which is the nonparametric … | 2013 |
| Multivariable input-output linearization sliding mode control of DFIG based wind energy conversion system | Akbar Tohidi, Ali Shamsaddinlou, Ali Khaki Sedigh | In this paper, obtaining of maximum active and reactive output power for wind turbines equipped with a double fed induction generator using stator-flux-oriented vector control based on novel multivariable input output linearization sliding mode control presented. The main control problem is the estimation of maximum power operating points of wind turbine under stochastic wind velocity profiles and tracking them using conventional offline and innovative adaptive online method. In this control strategy the wind speed and consequent aerodynamics torque is considered as the disturbance. Results under different operating conditions show the superior performance of the proposed online input-output linearization sliding mode technique. | 2013 |
| Performance evaluation of non-minimum phase linear control systems with fractional order partial pole-zero cancellation | N Khalili Zadeh Mahani, A Khaki Sedigh, F Merrikh Bayat | It has been known that, real right half plane (RHP) zeros imply serious limitations on the performance of nonminimum phase systems. Feedback cannot remove these limitations, mainly because RHP zeros cannot be cancelled by unstable poles of the controller since such a cancellation leads to internal instability. Hence, the idea of using fractional order systems in partial cancellation of the RHP zeros without leading to internal instability is studied. In this paper, the partial cancellation of RHP zeros with RHP poles is proposed using the fractional calculus approach. It is shown that undershoot and settling time of the compensated system is improved. Using suitable optimum criterion, it is shown that the performance of closed loop system can be relatively improved. Simulation results are used to show the effectiveness of the proposed methodology. | 2013 |
| A new control allocation methodology based on the pseudo inverse along the null space | Davoud Bozorgnia, Ali Khaki Sedigh | A relatively simple and exact solution of a control allocation algorithm with low computational cost can greatly influence a multivariable system performance. In this paper the pseudo inverse approach is used to achieve the exact answer. Then, the solution is modified by the null space of control matrix in order to satisfy the constraints. Therefore, we could hold the simplicity and exactness of the pseudo inverse approach and remove its deficiency by the proposed methodology. Furthermore, a simulation is provided to show the main characteristics of the proposed method and its superiority. | 2013 |
| Two new methods for DNA splice site prediction based on neuro-fuzzy network and clustering | Fahimeh Moghimi, Mohammad Taghi Manzuri Shalmani, Ali Khaki Sedigh, Mohammad Kia | Nowadays, genetic disorders, like cancer and birth defects, are a great threat to human life. Since the first noticing of these types of diseases, many efforts have been made and researches performed in order to recognize them and find a cure for them. These disorders affect genes and they appear as abnormal traits in a genetic organism. In order to recognize abnormal genes, we need to predict splice sites in a DNA signal; then, we can process the genetic codes between two continuous splice sites and analyze the trait that it represents. In addition to abnormal genes and their consequent disorders, we can also identify other normal human traits like physical and mental features. So the primary issue here is to estimate splice sites precisely. In this paper, we have introduced two new methods in using neuro-fuzzy network and clustering for DNA splice site prediction. In this method, instead of using raw data … | 2013 |
| Automatic model bank selection in multiple model identification of gas turbine dynamics | SeyedM Hosseini, Alireza Fatehi, Ali K Sedigh, Tor A Johansen | A multiple model structure of a prototype industrial gas turbine system is constructed under normal operation using a systematic method that incorporates non-linearity measure and H-gap metric tools with the multiple models technique. First, two new non-linearity indices for multiple input–multiple output systems are introduced and employed for decomposing the operating space of a gas turbine into some linear and non-linear modes. The non-linear modes may be further partitioned into some linear modes. The input and output data in each of the linear modes are used to construct an initial multiple model structure. In order to avoid the increase of the number of linear local models, the H-gap metric is extended to multiple input–multiple output systems and used to measure the similarity between linear local models and to merge the similar models. As a result, an algorithm is proposed for construction of multiple … | 2013 |
| On the structural optimization of a neural network model predictive controller | Mahsa Sadeghassadi, Alireza Fatehi, Ali Khaki Sedigh, SeyedMehrdad Hosseini | This paper provides a new algorithm for tuning the two most effective parameters in nonlinear model predictive control (NMPC). Tuning is performed in two steps. First, a new method based on Barron’s formula, the bicoherence nonlinearity test, and inphase-quadrature demodulation is proposed to determine the number of hidden layer neurons in a two-layer neural network. In the second step, a fuzzy algorithm is introduced to tune the input weight matrix in the objective function to make the tuning problem more practical and precise. To show the effectiveness of the proposed method, several examples are discussed including a simple flow process and a more complex pH neutralization problem. The method is also evaluated in the laboratory scale pressure and level processes. It is shown that the proposed method leads to tuning the number of neurons and the weight matrix with an acceptable performance. | 2013 |
| Adaptive fault tolerance in automotive vehicle using control allocation based on the pseudo inverse along the null space for yaw stabilization | Shahab Tohidy, Ali Khaki Sedigh | Yaw instability of automotive vehicles occurs dangerous accidents particularly while driving on wet or icy surfaces. Considering wet or icy situations as faults, fault tolerant controllers are suitable to handle the control of automotive vehicles. In order to have yaw stability and increasing maneuverability and safety of faulty systems, using control allocation methods are good choices. This paper proposes a control allocation method based on the pseudo inverse along the null space of the control matrix (PAN) to establish lateral stabilization in automotive vehicle. | 2013 |
| Selection of sensors for hydro-active suspension system of passenger car with input–output pairing considerations | Ehsan Sarshari, Ali Khaki Sedigh | With respect to weight, energy consumption, and cost constraints, hydro-active suspension system is a suitable choice for improving vehicle ride comfort while keeping its handling. The aim of sensors selection is determining number, location, and type of sensors, which are the best for control purposes. Selection of sensors is related to the selection of measured variables (outputs). Outputs selection may limit performance and also affect reliability and complexity of control systems. In the meanwhile, hardware, implementation, maintenance, and repairing costs can be affected by this issue. In this study, systematic methods for selecting the viable outputs for hydro-active suspension system of a passenger car are implemented. Having joint robust stability and nominal performance of the closed loop is the main idea in this selection. In addition, it is very important to use these methods as a complementation for system … | 2013 |
| Fault tolerant fuzzy control allocation for overactuated systems | Shahab Tohidy, Ali Khaki Sedigh | An adaptive fault tolerant control systems are vital in many industrial systems. Redundancy is a practical approach to decrease the effects of faults in systems. Redundancy in actuators can also increase system reliability and flexibility. This paper proposes a fuzzy control allocation method that can allocate control signal among actuators to increase reliability and maneuverability in healthy conditions and tolerating faults in faulty conditions. Using fuzzy logic is an intelligent way to adaptively change the gains of control allocation in different operating conditions. | 2013 |
| Study of multiple model predictive control on a pH neutralization plant | Ali Shamsaddinlou, Alireza Fatehi, Ali Khaki Sedigh, Mohammad Mahdi Karimi | Nonlinear behavior and disturbance sensitivity of the pH processes causes them to be known as an appropriate test bench for advanced controllers. Because of special behavior and varying parameters of pH processes, Multiple Model Predictive Controllers (MMPC) outperform other controllers from both regulation and disturbance rejection points of views. Two new supervisory methods based on prediction error and fuzzy weighting for MMPC are presented. Better regulation in special condition and most excellent disturbance rejection in comparison to other MMPC methods are achieved. | 2013 |
| Robust multivariable controller design with the simultaneous H2/H∞/µ for a single person aircraft | Javad Mashayekhi Fard, Mohammad Ali Nekoui, Ali Khaki Sedigh, Roya Amjadifard | In a physical system several targets are normally being considered in which each one of nominal and robust performance has their own strengths and weaknesses. In nominal performance case, system operation without uncertainty has decisive effect on the operation of system, whereas in robust performance one, operation with uncertainty will be considered. The purpose of this paper is a balance between nominal and robust performance of the state feedback. The new approach of present paper is the combination of two controllers of μ and H2/H∞. The controller for robust stability status, nominal performance, robust performance and noise rejection are designed simultaneously. The controller will be achieved by solving constraint optimization problem. The paper uses a simultaneous H2/H∞/µ robust multivariable controller design over an X-29 Single Person aircraft. This model has three inputs and three outputs, where the state space equations of the system correspond to an unstable one. Simulation results show the effectiveness and benefits of the method. | 2013 |
| Robust water level control of the U-tube steam generator | O Safarzadeh, A Khaki-Sedigh, AS Shirani | In this paper, a new practical robust water level control system for the U-tube steam generator (UTSG) using the quantitative feedback theory (QFT) is proposed. The steam generator is a nonlinear uncertain plant. However, the steam generator behaves as a linear uncertain and nonminimum phase plant at its different operating points, which makes its control a challenging problem. The control problem is to design controllers such that the closed-loop plant satisfies the robust stability, disturbance rejection, and robust tracking specifications that are derived from a desired steam generator performance. In the QFT design methodology, these specifications are satisfied by generating the plant templates, the composite bounds, and a nominal plant loop shaping procedure to satisfy these bounds. Simulation results reveal that the designed QFT water level controllers will ensure all the designers’ closed-loop … | 2013 |
| Robust μ-modification output feedback adaptive control for systems with input saturation | Babak Ebrahimi Lame, Hamid Khaloozadeh, Ali Khaki Sedigh | In this paper, for a class of linear systems with unknown parameters, a direct model reference adaptive control scheme in output feedback form has been presented, which assures stable adaptation in the presence of input saturation. Also, under certain assumptions one can guarantee that the adaptive control signal will avoid input saturation. In addition, by considering that the error model is in a parametric model form, robust adaptive control is used to improve robustness of systems in the presence of bounded disturbances. This is achieved by using the a-modification method. Simulation of an output feedback system with relative degree 2 verifies the results given in the paper. | 2013 |
| Predictive Controlled GSP Performance Improvement with an Integrated ℋ2/ℋ∞ | Mahdy Rezaei Darestani, Ali KhakiSedigh | To improve the performance of a robust control, in presence of internal or external disturbance and uncertainties, to make a smooth tracking and elimination of high frequency disturbances especially in accurate systems with minimum power consumption an integration of robust optimal controller considered. Here, derivation and implementation of the proposed controller based on the combination of and controllers to use their characteristics against unknown disturbances is considered. The proposed controller was implemented on a 3 axis gyro-stabilized MIMO platform. The results which express the control designer desires, compared to the implemented NLPID and a single controller on the same system. | 2013 |
| PREDICTIVE CONTROLLED GSP PERFORMANCE IMPROVEMENT WITH AN INTEGRATED H2/H∞ | DARESTANI M REZAEI, AA NIKKHAH, SEDIGH A KHAKI | An integrated robust optimal control is presented to enhance the closed loop performance in the presence of disturbance and uncertainties, to ensure smooth tracking and elimination of high frequency disturbances especially in accurate systems with minimum power consumption. Simulation result of the proposed controller based on the combination of H 2 and H¥ controllers is used to show the effectiveness of the proposed methodology. A 3 axis gyro-stabilized MIMO platform is considered and the results of the NLPID and a single H¥ controller are compared with the proposed H¥/H 2 controller. | 2013 |
| Forecasting of short-term traffic-flow based on improved neurofuzzy models via emotional temporal difference learning algorithm | Javad Abdi, Behzad Moshiri, Baher Abdulhai, Ali Khaki Sedigh | Bounded rationally idea, rather that optimization idea, have result and better performance in decision making theory. Bounded rationality is the idea in decision making, rationality of individuals is limited by the information they have, the cognitive limitations of their minds, and the finite amount of time they have to make decisions. The emotional theory is an important topic presented in this field. The new methods in the direction of purposeful forecasting issues, which are based on cognitive limitations, are presented in this study. The presented algorithms in this study are emphasizes to rectify the learning the peak points, to increase the forecasting accuracy, to decrease the computational time and comply the multi-object forecasting in the algorithms. The structure of the proposed algorithms is based on approximation of its current estimate according to previously learned estimates. The short term traffic flow forecasting … | 2012 |
| Adaptive neural network control of bilateral teleoperation with constant time delay | A Forouzantabar, HA Talebi, AK Sedigh | This paper proposes a novel approach for bilateral teleoperation systems with a multi degrees-of-freedom (DOF) nonlinear robotic system on the master and slave side with constant time delay in a communication channel. We extend the passivity based architecture to improve position and force tracking and consequently transparency in the face of offset in initial conditions, environmental contacts and unknown parameters such as friction coefficients. The proposed controller employs a stable neural network on each side to approximate unknown nonlinear functions in the robot dynamics, thereby overcoming some limitations of conventional controllers such as PD or adaptive controllers and guaranteeing good tracking performance. Moreover, we show that this new neural network controller preserves the control passivity of the system. Simulation results show that NN controller tracking performance is … | 2012 |
| Bilateral control of master–slave manipulators with constant time delay | A Forouzantabar, HA Talebi, AK Sedigh | This paper presents a novel teleoperation controller for a nonlinear master–slave robotic system with constant time delay in communication channel. The proposed controller enables the teleoperation system to compensate human and environmental disturbances, while achieving master and slave position coordination in both free motion and contact situation. The current work basically extends the passivity based architecture upon the earlier work of Lee and Spong (2006) [14] to improve position tracking and consequently transparency in the face of disturbances and environmental contacts. The proposed controller employs a PID controller in each side to overcome some limitations of a PD controller and guarantee an improved performance. Moreover, by using Fourier transform and Parseval’s identity in the frequency domain, we demonstrate that this new PID controller preserves the passivity of the system … | 2012 |
| Sufficient condition for stabilization of linear time invariant fractional order switched systems and variable structure control stabilizers | Saeed Balochian, Ali Khaki Sedigh | This paper presents the stabilization problem of a linear time invariant fractional order (LTI-FO) switched system with order 1| 2012 |
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| Multiple model bank selection based on nonlinearity measure and H-gap metric | SeyedMehrdad Hosseini, Alireza Fatehi, Tor Arne Johansen, Ali Khaki Sedigh | This paper provides a systematic method for model bank selection in multi-linear model analysis for nonlinear systems by presenting a new algorithm which incorporates a nonlinearity measure and a modified gap based metric. This algorithm is developed for off-line use, but can be implemented for on-line usage. Initially, the nonlinearity measure analysis based on the higher order statistic (HOS) and the linear cross correlation methods are used for decomposing the total operating space into several regions with linear models. The resulting linear models are then used to construct the primary model bank. In order to avoid unnecessary linear local models in the primary model bank, a gap based metric is introduced and applied in order to merge similar linear local models. In order to illustrate the usefulness of the proposed algorithm, two simulation examples are presented: a pH neutralization plant and a … | 2012 |
| Target tracking of autonomous robotic vehicles using range‐only measurements: a switched logic‐based control strategy | Omid Namaki‐Shoushtari, A Pedro Aguiar, Ali Khaki‐Sedigh | This paper considers the pursuing or target tracking problem where an autonomous robotic vehicle is required to move towards a maneuvering target using range‐only measurements. We propose a switched logic‐based control strategy to solve the pursuing problem that can be described as comprising a continuous cycle of two distinct phases: (1) the determination of the bearing, and (2) the steering control of the vehicle to follow the direction computed in the previous step while the range is decreasing. We provide guaranteed conditions under which the switched closed‐loop system achieves convergence of the relative distance error to a small neighborhood around zero. Simulation results are presented and discussed.Copyright © 2011 John Wiley & Sons, Ltd. | 2012 |
| PID controller tuning using multi-objective optimization based on fused genetic-immune algorithm and immune feedback mechanism | Maryam Khoie, Karim Salahshoor, Ehsan Nouri, Ali Khaki Sedigh | In this paper, a Genetic-AIS (Artificial Immune System) algorithm is introduced for PID (Proportional-Integral-Derivative) controller tuning using a multi-objective optimization framework. This hybrid Genetic-AIS technique is faster and accurate compared to each individual Genetic or AIS approach. The auto-tuned PID algorithm is then fused in an Immune feedback law based on a nonlinear proportional gain to realize a new PID controller. Immune algorithm presents a promising scheme due to its interesting features such as diversity, distributed computation, adaptation and self monitoring. Accordingly, this leads to a more effective Immune-based tuning than the conventional PID tuning schemes benefiting a multi-objective optimization prospective. Integration of Genetic-AIS algorithm with Immune feedback mechanism results into a robust PID controller which is ultimately evaluated via simulation control test … | 2012 |
| Robustness analysis and tuning of generalized predictive control using frequency domain approaches | P Sarhadi, K Salahshoor, A Khaki-Sedigh | The paper presents a new frequency-domain methodology to explicitly address the robustness margins for analysis and tuning of generalized predictive control (GPC). The GPC is formulated in two-degree-of-freedom configuration to allow for simultaneous execution of robustness analysis and frequency characteristic shaping. The underlying idea is to present a robust tuning scheme for GPC scheme by synthesizing some sensitivity functions in discrete-time domain, quantifying the relevant cause-and-effect perturbations, in order to shape them so that the effects of influences can be reduced in a specific frequency range. Several frequency-domain templates have been introduced to practically demonstrate usefulness of output, noise, and input sensitivity functions as complementing analysis tools for robust tuning of GPC. The proposed method ensures robust adjustments of the non-trivial tuning of GPC free … | 2012 |
| Stabilization of chaos systems described by nonlinear fractional-order polytopic differential inclusion | Saeed Balochian, Ali Khaki Sedigh | In this paper, sliding mode control is utilized for stabilization of a particular class of nonlinear polytopic differential inclusion systems with fractional-order-0< q< 1. This class of fractional order differential inclusion systems is used to model physical chaotic fractional order Chen and Lu systems. By defining a sliding surface with fractional integral formula, exploiting the concept of the state space norm, and obtaining sufficient conditions for stability of the sliding surface, a special feedback law is presented which enables the system states to reach the sliding surface and consequently creates a sliding mode control. Finally, simulation results are used to illustrate the effectiveness of the proposed method. | 2012 |
| Robust tracking of a class of perturbed nonlinear systems via multivariable nested sliding mode control | Aras Adhami-Mirhosseini, Mohammad J Yazdanpanah, Ali Khaki-Sedigh | In this paper, a new methodology for robust controller design in nonlinear multivariable systems is suggested to guarantee asymptotic output tracking. The systems under consideration are perturbed by functionally bounded matched and unmatched uncertainties/perturbations and assumed to be described in the strict-feedback form. The main idea of the methodology is based on the combination of conventional sliding mode control and backstepping algorithm. The proposed controller called nested sliding mode controller that is obtained through a stepwise algorithm. It has the ability of rejecting nonvanishing perturbations by using dynamic switches, unlike conventional and other hierarchical sliding mode design methods. Performance is studied through theorems and verified by two numerical examples. | 2012 |
| Decentralized supervisory based switching control for uncertain multivariable plants with variable input–output pairing | Omid Namaki-Shoushtari, Ali Khaki-Sedigh | In this paper, the design of decentralized switching control for uncertain multivariable plants is considered. In the proposed strategy, the uncertainty region is divided into smaller regions with a nominal model and specific control structure. The underlying design is based on the quantitative feedback theory (QFT). It is assumed that a MIMO-QFT controller exists for robust stability and performance of the individual uncertain sets. The proposed control structure is made up by these local decentralized controllers, which commute among themselves in accordance with the decision of a high level decision maker called the supervisor. The supervisor makes the decision by comparing the local models’ behaviors with the one of the plant and selects the controller corresponding to the best fitted model. A hysteresis switching logic is used to slow down the switching to guarantee the overall closed loop stability. It is shown that … | 2012 |
| Robust adaptive actuator failure compensation controller for systems with unknown time-varying state delays | Marzieh Kamali, Javad Askari, Farid Sheikholeslam, Ali Khaki Sedigh | An output feedback model reference adaptive controller is developed for a class of linear systems with multiple unknown time-varying state delays and in the presence of actuator failures. The adaptive controller is designed based on SPR-Lyapunov approach and is robust with respect to multiple unknown time-varying plant delays and to an external disturbance with unknown bounds. Closed-loop system stability and asymptotic output tracking are proved using suitable Lyapunov-Krasovskii functional and Simulation results are provided to demonstrate the effectiveness of the proposed controller. | 2012 |
| Lyapunov based multiple model predictive control: An LMI approach | Mohammad Abdollahpouri, Ali Khaki-Sedigh, Alireza Fatehi | A combined approach for bumpless transfer multiple model predictive control (Multiple MPC) is proposed based on the Lyapunov function. State-space representation is used to design the controllers and the Lyapunov approach is employed to ensure closed loop stability. The proposed method uses both an intermediate controller and a bumpless mechanism in a unified configuration based on the stability analysis. Previous works on the bumpless multiple MPC design do not ensure closed loop stability, while the mechanism presented in this paper ensures both closed loop stability and applicable control performance for industrial processes. Finally, efficiency of the proposed method is validated by simulation results on non-isothermal continuous stirred-tank reactor (CSTR) system. | 2012 |
| Enhancement of Robust Tracking Performance via Switching Supervisory Adaptive Control | SHOUSHTARI O NAMAKI, SEDIGH A KHAKI | When the process is highly uncertain, even linear minimum phase systems must sacrifice desirable feedback control benefits to avoid an excessive ‘cost of feedback’, while preserving the robust stability. In this paper, the control structure of supervisory based switching Quantitative Feedback Theory (QFT) control is proposed to control highly uncertain plants. According to this strategy, the uncertainty region is suitably divided into smaller regions. It is assumed that a QFT controller-prefilter exits for robust stability and robust performance of the individual uncertain sets. The proposed control architecture is made up by these local controllers, which commute among themselves in accordance with the decision of a high level decision maker called the supervisor. The supervisor makes the decision by comparing the candidate local model behavior with the one of the plant and selects the controller corresponding to the best fitted model. A hysteresis switching logic is used to slow down switching for stability reasons. Besides, each controller is designed to be stable in the whole uncertainty domain, and as accurate in command tracking as desired in its uncertainty subset to preserve the robust stability from any failure in the switching. | 2012 |
| Robustification of input redundant feedback systems using robust actuator weighting in the control allocation problem | Javad Ahmadi, Ali Khaki-Sedigh, Abdolreza Ohadi | In this article, a new methodology for robust actuator weighting in the control allocation (CA) problem of input redundant feedback systems is addressed. The methodology is based on the control structural properties of the plant which were previously used for control configuration selection. Robust performance (RP) measures including H ∞ norm and structured singular value of the closed-loop system are used in this article. The capability of the approach is proven with application to lateral dynamics control of the vehicle over-actuated with front and rear steering systems. Employing the RP measures, it is concluded that the vehicle feedback control with front steering angles gives superior RP properties in comparison with the feedback loop of the rear steering angles. Based on these results, the penalty weightings in the cost function of the CA unit are determined. Simulation results based on nonlinear seven … | 2012 |
| Adaptive control of the singularly perturbed chaotic systems based on the scale time estimation by keeping chaotic property | Mozhgan Mombeini, Ali Khaki Sedigh, Mohammad Ali Nekoui | In this paper, a new approach to the problem of stabilizing a chaotic system is presented. In this regard, stabilization is done by sustaining chaotic properties of the system. Sustaining the chaotic properties has been mentioned to be of importance in some areas such as biological systems. The problem of stabilizing a chaotic singularly perturbed system will be addressed and a solution will be proposed based on the OGY (Ott, Grebogi and Yorke) methodology. For the OGY control, Poincare section of the system is defined on its slow manifold. The multi-time scale property of the singularly perturbed system is exploited to control the Poincare map with the slow scale time. Slow scale time is adaptively estimated using a parameter estimation technique. Control with slow time scale circumvents the need to observe the states. With this strategy, the system remains chaotic and chaos identification is possible with online calculation of lyapunov exponents. Using this strategy on ecological system improves their control in three aspects. First that for ecological systems sustaining the dynamical property is important to survival of them. Second it removes the necessity of insertion of control action in each sample time. And third it introduces the sufficient time for census. | 2012 |
| Decentralized MRAC for Large Scale Systems with Input and State Delays | Syed Hamid Hashemipour, Nastrn Vasegh, Ali Khaki Sedigh | In this paper, the problem of decentralized model reference adaptive control (MRAC) for a class of large scale systems with time varying delay in interconnected term and input and state delays is studied. To compensate the effect of input delay indirectly, a Smith predictor built on. To handle the effects of the time delays in input, the adaptive controller part includes two auxiliary dynamic filters with time varying gains. Under a usual assumption that the interconnections are assumed to be Lipschitz in its variables and uniformly in time with unknown Lipschitz gains, the difficulties from unknown interconnections are dealt. A generalized error is defined and by a suitable Lyapunov function, an adaptive controller is designed to stabilize it. Decentralized adaptive feedback controller can render the generalized error system uniformly ultimately bounded stable is designed. Finally, a numerical example is given to demonstrate the feasibility and effectiveness of the proposed design techniques. 1 | 2012 |
| An Indirect Adaptive Predictive Control with Augmented UD Identifier for Linear Time Varying Systems | Pouria Sarhadi, Karim Salahshoor, Ali Khaki-Sedigh | In this paper, an indirect adaptive generalized predictive controller (GPC) is proposed by incorporating an augmented UD identifier (AUDI), based on Bierman’s UD factorization algorithm. The developed adaptive control scheme is mainly aimed to deal with systems having linear time varying (LTV) dynamic characteristics. A series of simulation studies has been conducted to reveal the effectiveness of the developed adaptive control scheme to cope with such time varying dynamic profiles. The obtained results illustrate the controller robustness against both external disturbances and parameters uncertainties. | 2012 |
| Implementation of an Improved Performance Integral H_2/H_∞ Combined Predictive Control on a GSP | Mahdy Rezaei Darestani, AmirAli Nikkhah, Ali KhakiSedigh | Abstract to enhance the closed loop performance in presence of disturbance, uncertainties and delay a double loop mixture of MPC and robust controller is proposed. This double loop controller ensures smooth tracking for a 3-axis gyro-stabilized platform which has delay intrinsically. This control idea is suggested to eliminate high frequency disturbances and minimize steady state error with minimum power consumption in simulation and experiment. Proposed controller based on the combination of ℋ2 and ℋ∞ controllers in the inner control loop shows the robustness of the proposed methodology. In the outer loop to have a good tracking performance, an integrated MPC is used to handle delay in system dynamics. Also, the main idea for dealing with uncertainties is using integral and derivative of platform attitude. In the proposed platform, the ℋ∞ controller is compared with ℋ∞/ℋ2 controller in KNTU laboratory in theory and experiment. Results of experimental set up shows the same reaction of two controllers against disturbance and uncertainties in delayed system. | 2012 |
| Modelling and Control of Four-Wheel Anti-lock Braking System | MA Nekoui, A Khaki Sedigh | Minimal stopping distance, guaranteed steering ability and stability are the three most important purposes in Anti-lock Braking System (ABS) realm. The ABS system is a nonlinear, time variant and multivariable system with some uncertainties. Some research work has been carried out on ABS control systems using intricate methods which are expensive to implement. In this paper at the first step the system interference is decreased via decoupling matrix and the ABS is controlled with a robust diagonal controller. In fact, a decentralized control technique is used for our ABS control mechanism. At the second step we exploit a multivariable technique in linear control to attack the problem. This is the Designed Linear Control with Multivariable Technique. The Optimal Eigenstructure Assignment with Genetic Algorithm (GA) method is also applied. Simulation and comparison studies are used to show the effectiveness of … | 2012 |
| Modelling and Control of Four-Wheel Anti-lock Braking System | Javad Mashayekhi Fard, Mohammad Ali Nekoui, Ali Khaki Sedigh | Minimal stopping distance, guaranteed steering ability and stability are the three most important purposes in Anti-lock Braking System (ABS) realm. The ABS system is a nonlinear, time variant and multivariable system with some uncertainties. Some research work has been carried out on ABS control systems using intricate methods, which are expensive to implement. In this paper at the first step, the system interference is decreased via decoupling matrix and the ABS is controlled with a robust diagonal controller. In fact, a decentralized control technique is used for our ABS control mechanism. At the second step, we exploit a multivariable technique in linear control to attack the problem. This is the Designed Linear Control with Multivariable Technique. The Optimal Eigenstructure assignment with the Genetic Algorithm (GA) method is also applied. Simulation and comparison studies are used to show the effectiveness of the proposed methods. | 2012 |
| An Algorithm for Multi-Realization of Nonlinear MIMO Systems | Soodeh Faraji, Ali Khaki Seddigh | This paper presents a theoretical approach to implementation of the “Multi-realization of nonlinear MIMO systems”. This method aims to find state-variable realization for a set of systems, sharing as many parameters as possible. In this paper a special nonlinear multi-realization problem, namely the multi-realization of feedback linearizable nonlinear systems is considered and an algorithm for achieving minimal stably-based multi-realization of a set of nonlinear feedback linearizable systems is introduced. An example that illustrates this algorithm is also presented | 2012 |
| Analysis of Two Time Scale Property of Singularly Perturbed System on Chaotic Attractor | Mozhgan Mombeini, Ali Khaki Sedigh, Mohammad Ali Nekoui | The idea that chaos could be a useful tool for analyze nonlinear systems considered in this paper and for the first time the two time scale property of singularly perturbed systems is analyzed on chaotic attractor. The general idea introduced here is that the chaotic systems have orderly strange attractors in phase space and this orderly of the chaotic systems in subscription with other classes of systems can be used in analyses. Here the singularly perturbed systems are subscripted with chaotic systems. Two time scale property of system is addressed. Orderly of the chaotic attractor is used to analyze two time scale behavior in phase plane. | 2012 |
| An Improved Input-output Pairing Method based on Concept of Energy | A Ahmadi-Tabatabaei, A Fatehi, A Khaki-Sedigh | In this paper input-output pairing is done based on concept of energy. Parseval theorem and cross-covariance samples of input-output are used for estimation of energy. After approximating interaction energy between input and output of the plant, input-output pairing is fulfilled. Through examples, it is illustrated that proposed method is appropriate for input-output pairing. The result is compared with Effective Relative Energy Array (EREA) as another energy based approach for input-output pairing. | 2012 |
| Combined Enhanced LMI Charactrization and Parametric Eigenstructure Assignment Using Static Output Feedback | Amir Parviz Valadbeygi, Ali Khaki Sedigh, Saeed Hosseinnia | This paper proposes mixed eigenstructure assignment with H∞ constraint when the states are not measurable. In this case, full state feedback is not permissible. So eigenstructure assignment by output feedback is considered. According to enhanced linear matrix inequality (LMI) and parametric eigenstructure assignment, we propose a method in terms of linear matrix inequality (LMI). This LMI can be easily solved by the Yalmip or LMI toolbox. | 2012 |
| DECENTRALIZED MRAC FOR LARGE SCALE SYSTEMS WITH INPUT AND STATE DELAYS | SEYED HAMID HASHEMI, NASTRN VASEGH, SEDIGH ALI KHAKI | In this paper, the problem of decentralized model reference adaptive control (MRAC) for a class of large scale systems with time varying delay in interconnected term and input and state delays is studied. To compensate the effect of input delay indirectly, a Smith predictor built on. To handle the effects of the time delays in input, the adaptive controller part includes two auxiliary dynamic filters with time varying gains. Under a usual assumption that the interconnections are assumed to be Lipschitz in its variables and uniformly in time with unknown Lipschitz gains, the difficulties from unknown interconnections are dealt. A generalized error is defined and by a suitable Lyapunov function, an adaptive controller is designed to stabilize it. Decentralized adaptive feedback controller can render the generalized error system uniformly ultimately bounded stable is designed. Finally, a numerical example is given to demonstrate the feasibility and effectiveness of the proposed design techniques. | 2012 |
| IMPLEMENTATION OF AN IMPROVED PERFORMANCE INTEGRAL H2/H∞ COMBINED PREDICTIVE CONTROL ON A GSP | DARESTANI MAHDY REZAEI, AMIR ALI NIKKHAH, SEDIGH ALI KHAKI | to enhance the closed loop performance in presence of disturbance, uncertainties and delay a double loop mixture of MPC and robust controller is proposed. This double loop controller ensures smooth tracking for a 3-axis gyro-stabilized platform which has delay intrinsically. This control idea is suggested to eliminate high frequency disturbances and minimize steady state error with minimum power consumption in simulation and experiment. Proposed controller based on the combination of H 2 and H¥ controllers in the inner control loop shows the robustness of the proposed methodology. In the outer loop to have a good tracking performance, an integrated MPC is used to handle delay in system dynamics. Also, the main idea for dealing with uncertainties is using integral and derivative of platform attitude. In the proposed platform, the H¥ controller is compared with H¥/H 2 controller in KNTU laboratory in theory and experiment. Results of experimental set up shows the same reaction of two controllers against disturbance and uncertainties in delayed system. | 2012 |
| Training ANFIS system with DE algorithm | Allahyar Z Zangeneh, Mohammad Mansouri, Mohammad Teshnehlab, Ali K Sedigh | In this study, a new type of training the adaptive network-based fuzzy inference system (ANFIS) is presented by applying different types of the Differential Evolution branches. The TSK-type consequent part is a linear model of exogenous inputs. The consequent part parameters are learned by a gradient descent algorithm. The antecedent fuzzy sets are learned by basic differential evolution (DE/rand/1/bin) and then with some modifications in it. This method is applied to identification of the nonlinear dynamic system, prediction of the chaotic signal under both noise-free and noisy conditions and simulation of the two-dimensional function. Instead of DE/rand/1/bin, this paper suggests the complex type (DE/current-to-best/1+1/bin & DE/rand/1/bin) on predicting of Mackey-glass time series and identification of a nonlinear dynamic system revealing the efficiency of proposed structure. Finally, the method is compared with … | 2011 |
| Tuning of dynamic matrix controller for FOPDT models using analysis of variance | Peyman Bagheri, Ali Khaki-Sedigh | Dynamic Matrix Control (DMC) is well known in the MPC family and has been implemented in many industrial processes. In all the MPC methods, tuning of controller parameters is a key step in successful control system performance. An analytical tuning expression for DMC is derived using the analysis of variance (ANOVA) methodology and nonlinear regression. It is assumed that the plants under consideration can be modeled by a First Order plus Dead Time (FOPDT) linear model. This facilitates the derivation of a closed form formulae for the tuning procedure. The proposed method is tested via simulations and experimental work. The plant chosen for practical implementation of the proposed tuning strategy is a nonlinear laboratory scale pH plant. Also, comparison results are provided to show the effectiveness of this method. | 2011 |
| Identification and robust water level control of horizontal steam generators using quantitative feedback theory | O Safarzadeh, A Khaki-Sedigh, AS Shirani | In this paper, a robust water level control system for the horizontal steam generator (SG) using the quantitative feedback theory (QFT) method is presented. To design a robust QFT controller for the nonlinear uncertain SG, control oriented linear models are identified. Then, the nonlinear system is modeled as an uncertain linear time invariant (LTI) system. The robust designed controller is applied to the nonlinear plant model. This nonlinear model is based on a locally linear neuro-fuzzy (LLNF) model. This model is trained using the locally linear model tree (LOLIMOT) algorithm. Finally, simulation results are employed to show the effectiveness of the designed QFT level controller. It is shown that it will ensure the entire designer’s water level closed loop specifications. | 2011 |
| Variable structure control of linear time invariant fractional order systems using a finite number of state feedback law | Saeed Balochian, Ali Khaki Sedigh, Asef Zare | In this paper, an approach based on the variable structure control is proposed for stabilization of linear time invariant fractional order systems (LTI-FOS) using a finite number of available state feedback controls, none of which is capable of stabilizing the LTI-FOS by itself. First, a system with integer order derivatives is defined and its existence is proved, which has stability equivalent properties with respect to the fractional system. This makes it possible to use Lyapunov function and convex analysis in order to define the sliding sector and develop a variable structure control which enables the switching between available control gains and stabilizing the fractional order system. | 2011 |
| Improved dead zone modification for robust adaptive control of uncertain linear systems described by input-output models with actuator faults | Behnam Allahverdi Charandabi, Farzad R Salmasi, Ali Khaki Sedigh | This article considers an improvement in dead zone modification scheme for robust model-reference adaptive control of SISO and TITO systems, described by input-output uncertain linear models with actuator faults. In the conventional approach, adaptation of the controller parameters is ceased in the dead zone, which leads to steady state tracking error. This problem is resolved by tuning specific controller parameters inside the dead zone. The stability of the closed loop system and tracking of step commands are verified analytically. A comparative numerical simulation is performed to illustrate the effectiveness of the proposed scheme in control of an engine-dynamometer system. | 2011 |
| Stabilization of fractional order systems using a finite number of state feedback laws | Saeed Balochian, Ali Khaki Sedigh, Mohammad Haeri | In this paper, the stabilization of linear time-invariant systems with fractional derivatives using a limited number of available state feedback gains, none of which is individually capable of system stabilization, is studied. In order to solve this problem in fractional order systems, the linear matrix inequality (LMI) approach has been used for fractional order systems. A shadow integer order system for each fractional order system is defined, which has a behavior similar to the fractional order system only from the stabilization point of view. This facilitates the use of Lyapunov function and convex analysis in systems with fractional order 1| 2011 |
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| Stabilization of multi-input hybrid fractional-order systems with state delay | Saeed Balochian, Ali Khaki Sedigh, Asef Zare | In this paper, the stabilization of a particular class of multi-input linear systems of fractional order differential inclusions with state delay using variable structure control is considered. First, the sliding surface with a fractional order integral formula is defined, and then the sufficient conditions for stability of the sliding surface are derived. Also, the concepts related to sliding control stabilization of differential inclusion systems with integer order are extended to differential inclusion systems with fractional order 0| 2011 |
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| A hybrid EKF-fuzzy approach to fault detection and isolation of industrial gas turbines | Amin Salar, Ali Khaki Sedigh, SeyedMehrdad Hosseini, Hiwa Khaledi | Based on the Gas Path Analysis (GPA) method, nonlinear estimation and fuzzy classification theories, a comprehensive fault diagnosis system has been developed for an industrial Gas Turbine (GT). The hybrid method consists of two parts, in the first part noisy sensor output changes are translated to changes in the health parameters using an Extended Kalman Filter (EKF). In the second part the outputs of the EKF are used as the inputs of a fuzzy system. This system can isolate and evaluate the physical faults based on the predetermined rules obtained mostly from experimental data and aerothermodynamical simulations. The ratios of changes in different health parameters due to different faults and also the areas in the compressor most affected by these faults are the key factors for developing the rules. The Fuzzy Inference System (FIS) gives the fault locations in the compressor or turbine. Also, operator-friendly … | 2011 |
| Predictive control of a two degrees of freedom xy robot (satellite tracking pedestal) and comparing gpc and gipc algorithms for satellite tracking | A Ghahramani, T Karbasi, M Nasirian, A Khaki Sedigh | In this paper, two Generalized Predictive Control algorithms (GPC, GIPC) are used to control X, Y axes of a Two-Degrees-of-Freedom robot, which is a earth station antenna related to be the HDF pedestals (High Dynamic Full Motion Leo Satellite Tracking Pedestals). This system model is achieved by using the Dymola software that according to the comparisons which have been done is very close to the actual system model and has very high accuracy. Comparing the simulation results between GPC and GIPC, fewer tracking errors are observed for the latter while it is much better when it comes to the disturbance rejection criterion. | 2011 |
| Design of a switching PID controller for a magnetically actuated mass spring damper | Shabnam Armaghan, Arefeh Moridi, Ali Khaki Sedigh | In this paper the use of proportional-integral-derivative (PID) switching controllers is proposed for the control of a magnetically actuated mass-spring-damper system which is composed of two masses M1 and M2; each mass is jointed to its own spring. Two different modes occur during the system motion; a PID controller is designed for each mode and a switching logic is applied in order to recognize the system’s position to switch to the proper controller. Finally, simulation results are employed to show the performance of the proposed switched PID controller. Also, comparison results with the previously used model predictive controller (MPC) are provided. | 2011 |
| Predictive control of earth station antenna (XY pedestal) | A Ghahramani, T Karbasi, M Nasirian, A Khaki Sedigh | In this paper control of the xy pedestal axes has been studied which is a two degrees of freedom earth station antenna of pedestal HDF family group (High Dynamic Full Motion Leo Satellite Tracking Pedestals). This system model is achieved by using the Dymola software that according to the comparisons which have been done is very close to the actual system model and has very high accuracy. Purpose: is to track a LEO orbit satellite that of passing satellites and angles related to the antenna have been extracted path from KNTUSAT software. In carried out simulation, the operation of PI controller has been optimized, MPC and GPC has been studied. The results of comparison between simulation methods show that predictive controller has had fewer errors in satellite tracking and has been shown less control effort and also has had good behavior in disturbance rejection. | 2011 |
| Verification of intelligent control of a launch vehicle with HILS | M Rezaei Darestani, M Zareh, J Roshanian, A Khaki Sedigh | The reliability of an intelligent self tuning controller called the brain emotional learning based intelligent controller (BELBIC) to attitude control of a nonlinear launch vehicle (LV) simulation with hardware-in-the loop simulation (HILS) is studied. To set up the HIL system of the LV a six-degree of freedom simulation of the LV and a hydraulic actuator, which was used for the pitch channel thrust vector control (TVC) actuator of the LV, is performed. The results of the BELBIC controller with a fuzzy controller (FC) and a PID controller in this HILS of the LV to control the pitch channel of the LV have been compared. | 2011 |
| Design of switching control systems using control performance assessment index | Arefeh Moridi, Shabnam Armaghan, A Khaki Sedigh, Saleheh Choobkar | Switching control is employed in many adaptive control strategies to overcome difficulties encountered in the control design problems that cannot be routinely solved by conventional robust and adaptive control architectures. A key stage in switching control design is the switching logic. This paper proposes a new switching scheme based on the control performance index (CPI) concepts. The performance assessment index is primarily calculated using the Markov parameters of the closed loop transfer function to assess the closed loop performance of the regulatory and tracking control systems. It is shown that employing CPI can lead to proper switching between different controllers. Finally, simulation results are provided show the main points of the paper. | 2011 |
| Optimal number of neurons for a two layer neural network model of a process | Mahsa Sadegh Asadi, Alireza Fatehi, Mehrdad Hosseini, Ali Khaki Sedigh | Neural networks are known as powerful tools to represent the essential properties of nonlinear processes because of their global approximation property. However, a key problem in modeling nonlinear processes by neural networks is the determination of neuron numbers. In this paper, a data based strategy for determining number of hidden layer neurons based on the Barrons work, describing function analysis and bicoherence nonlinearity measure is proposed. The proposed algorithm is evaluated for a pH neutralization process. It is shown that this algorithm has acceptable results. | 2011 |
| An adaptive observer for linear systems with reduced adaptation laws and measurement faults | Amirhossein Nikoofard, Farzad R Salmasi, Ali Khaki Sedigh | In this note, an adaptive observer is considered for simultaneous estimation of the states and unknown parameters of linear stationary systems with faulty measurements. Since entries of system matrices are functions of only a few parameters, it is enough to tune those parameters, instead of adapting all entries. This leads to reduced adaptation laws. Moreover, the problem of measurement offset and gain faults are also considered. The stability and convergence of the proposed adaptive observer is investigated. Simulation results validate the performance of the proposed adaptive observer. | 2011 |
| Robust gas turbine speed control using QFT | Zoleikha Abdollahi Biron, Ali Khaki Sedigh, Roghiyeh Abdollahi Biron | This paper provides a Quantitative Feedback Theory (QFT) robust control design of a gas turbine in the presence of uncertain parameters. Frequency domain analysis, disturbance rejection properties for SISO and MIMO plants, are among the distinctive features of QFT. In this paper, a QFT robust controller satisfying the required performance despite uncertainties and various constraints on the control effort and process is designed. The nonlinear gas turbine simulator employed in this paper is based on the gas turbine thermodynamic characteristics presented within MATLAB-SIMULINK. The accuracy of this simulator has been examined through several tests by real gas turbine responses. | 2011 |
| A switched based control strategy for target tracking of autonomous robotic vehicles using range-only measurements | Omid Namaki-Shoushtari, A Pedro Aguiar, Ali Khaki Sedigh | In this paper we address the pursuing or target tracking problem where an autonomous robotic vehicle is required to move towards a maneuvering target using range-only measurements. A new switched based control strategy is proposed to solve the pursuing problem that can be described as comprising a continuous cycle of two distinct phases: i) the determination of the bearing, and ii) following the direction computed in the previous step while the range is decreasing. We provide conditions under which the switched closed-loop system achieves convergence of the relative distance error to a small neighborhood around zero. Simulation results are presented and discussed. | 2011 |
| Descriptive vector, relative error matrix, and interaction analysis of multivariable plants | Nima Monshizadeh-Naini, Alireza Fatehi, Ali Kahki-Sedigh | In this paper, we introduce a vector which is able to describe the Niederlinski Index (NI), Relative Gain array (RGA), and the characteristic equation of the relative error matrix. The spectral radius and the structured singular value of the relative error matrix are investigated. The cases where the perfect result of the Relative Gain Array, equal to the identity matrix, coincides with the least interaction in a plant are pointed out. Then, the Jury Algorithm is adopted to get some insight into interaction analysis of multivariable plants. In particular, for interaction analysis of 3×3 plants, simple yet promising conditions in terms of the Relative Gain Array and the NiederLinski Index are derived. Several examples are also discussed to illustrate the main points. | 2011 |
| Adaptive neural network control of bilateral teleoperation with time delay | A Forouzantabar, H Talebi, A Khaki Sedigh | This paper proposes a novel architecture for bilateral teleoperation with a master and slave nonlinear robotic systems under constant communication delays. We basically extend the passivity based coordination architecture to improve position and force tracking and consequently transparency in the face of offset in initial conditions, environmental contacts and unknown parameters such as friction coefficient. This structure provides robust stability against constant delay and guarantee position and force tracking. The proposed controller employ a stable neural network in each side to approximate unknown nonlinear functions in the robot dynamics, thereby overcoming some limitation of adaptive control and guarantee good performance. An adaptation algorithm is developed to train the NN controller in order to stabilize the whole system. Furthermore, it is demonstrate that the tracking error of desired trajectory and … | 2011 |
| A decomposition procedure to linearize the non-affine state space average model of STATCOM | Milad Moradpour, M Tavakoli Bina, A Khaki Sedigh, Moosa Ayati | Various studies have been devoted to modulation and control of power electronic systems. Modeling of such a system is often required for control purposes. One modeling approach is the standard state space average model (SSSAM), which considers switching behaviors of the converters. The developed SSSAM of the static compensators (STATCOM) describes a non-affine model that is hardly controllable. A decomposition procedure has been proposed in this paper to make this non-affine SSSAM like an affine model. First, a non-affine SSSAM is derived that includes an interconnected STATCOM to an equivalent Thevenin model of the network along with the load. Then, the proposed decomposition procedure is applied to the non-affine SSSAM, where the resultant affine SSSAM is simulated. Simulations are presented for both the non-affine and the proposed affine model, showing the performance of the … | 2011 |
| The correlation based method for input-output pairing | Adel Ahmadi Tabatabaei, Alireza Fatehi, Ali Khaki Sedigh | In this paper, a new approach for input-output pairing for stable and linear time invariant multivariable systems based on inputs-outputs correlation is introduced. Being independent from system’s model is the characteristic of the proposed method. It is demonstrated that both static and dynamic properties of the system regarded in the proposed method. Through examples, the accuracy of the proposed approach is investigated. Finally, an example is used to show that in some cases Effective Relative Gain Array (ERGA) leads to improper pairs while the proposed method achieves the appropriate pairs. | 2011 |
| Systems, Science & Technology | Khairul Anuar Mohamad Ismail Saad, Nurmin Bolong, Abu Bakar Abd Rahman, Vijay Arora, Ismail Saad, Divya Pogaku, Bablu K Ghosh, Kenneth Tze Kin Teo, Ahmed Al-Araji, Maysam F Abbod, Hamed Saffa Al-Raweshidy, Yit Kwong Chin, Aroland Mconie Jilui Kiring, Soo Siang Yang, Wei Yeang Kow, Wei Leong Khong, Hoe Tung Yew, Lorita Angeline, Chia Seet Chin, Neelakantan Prabhakaran, Bih Lii Chua | DESIGN AND SIMULATION ANALYSIS OF VERTICAL DOUBLE-GATE MOSFET (VDGM) STRUCTURE FOR NANO-DEVICE APPLICATION | 2011 |
| Design of Supervisory Based Switching QFT Controllers with Bumpless Transfer | Omid Namaki-Shoushtari, Ali Khaki Sedigh | In this paper, the problem of supervisory based switching Quantitative Feedback Theory (QFT) control is proposed for the control of highly uncertain plants. In the proposed strategy, the uncertainty region is divided into smaller regions with a nominal model. It is assumed that a QFT controller-prefilter exists for robust stability and performance of the smaller uncertainy subsets. The proposed control architecture is made up by these local controllers, which commute among themselves in accordance with the decision of a high level decision maker called the supervisor. The supervisor compares the candidate local model behaviors with the one of the real plant and selects the controller corresponding to the best fitted model. A hysteresis switching logic is used to slow down switching for stability reasons. It is shown that this strategy improves closed loop performance, and can also handle the uncertainty sets that cannot be tackled by a single QFT robust controller. The multirealization technique to implement a family of controllers is employed to achieve bumpless transfer. Simulation results show the effectiveness of the proposed methodology. | 2011 |
| Generalized predictive control and tuning of industrial processes with second order plus dead time models | AR Neshasteriz, A Khaki Sedigh, H Sadjadian | In this paper, an extension of the modified generalized predictive control (GPC) algorithm and a tuning strategy is presented. To take the plant dynamics such as under damped behavior and the effect of zeros into account, extension to the second order plus dead time (SOPDT) of the first order plus dead time (FOPDT) modified GPC method is proposed. It is shown that this method is computationally undemanding. Also, implementation is more straightforward than conventional GPC algorithms. Moreover, the proposed tuning strategy enables a fast implementation of the GPC with regard to nominal stability and desired performance. The simplicity of this strategy and its wide applicability makes it readily accessible to practitioners for utilization. Multiple simulation results are provided to show the effectiveness of the proposed algorithm. | 2010 |
| An adjustable model reference adaptive control for a flexible launch vehicle | AM Khoshnood, J Roshanian, AA Jafari, A Khaki-Sedigh | Flexibility and aeroelastic behaviors in large space structures can lead to degradation of control system stability and performance. The model reference adaptive notch filter is an effective methodology used and implemented for reducing such effects. In this approach, designing a model reference for adaptive control algorithm in a flight device such as a launch vehicle is very important. In this way, the vibrations resulting from the structure flexibility mostly affects the pitch channel, and its influences on the yaw channel are negligible. This property is used and also the symmetrical behavior of the yaw and pitch channels. In this paper, by using this property and also the symmetrical behavior of the yaw and pitch channels, a new model reference using identification on the yaw channel is proposed. This model behaves very similar to the rigid body dynamic of the pitch channel and can be used as a model reference to … | 2010 |
| A subspace based method for time delay estimation | Jafar Shalchian, Ali Khaki-Sedigh, Alireza Fatehi | Time delays are common in industrial processes. The information about the delay value of any process is valuable for both identification and control procedures. Several methods have been suggested for time delay estimation (TDE) in the literature. We propose a simple method based on plant input-output data. The concept of this data driven method is from combination of two well known approaches: Time delay estimation from impulse response and subspace identification. This method can be easily implemented in Multi Input-Multi Output (MIMO) plants. Also, by analyzing the window of input-output data in an online fashion, we can utilize our proposed method for time varying delay case. To verify the effectiveness of our proposed method, the developed procedures are applied to a pH plant model, a MIMO system and a time delay varying scenario. Simulation results demonstrate the effectiveness of the … | 2010 |
| Comparison of RBF and MLP neural networks in short-term traffic flow forecasting | Javad Abdi, Behzad Moshiri, A Khaki Sedigh | Expanding mathematical models and forecasting the traffic flow is a crucial case in studying the dynamic behaviors of the traffic systems these days. Artificial Neural Networks (ANNs) are of the technologies presented recently that can be used in the intelligent transportation system field. In this paper, two different algorithms, the Multi-Layer Perceptron (MLP) and the Radial Basis Function (RBF) have been discussed. In the training of the ANNs, we use historic data. Then we use ANNs for forecasting a daily real time short-term traffic flow. The ANNs are trained by the Back-Propagation (BP) algorithm. The variable coefficients produced by temporal signals improve the performance of the BP algorithm. The temporal signals provide a new method of learning called Temporal Difference Back-Propagation (TDBP) learning. We demonstrate the capability and the performance of the TDBP learning method with the … | 2010 |
| Improving model-based gas turbine fault diagnosis using multi-operating point method | Amin Salar, Seyed Mehrdad Hosseini, Behnam Rezaei Zangmolk, Ali Khaki Sedigh | A comprehensive gas turbine fault diagnosis system has been designed using a full nonlinear simulator developed in Turbotec company for the V94.2 industrial gas turbine manufactured by Siemens AG. The methods used for detection and isolation of faulty components are gas path analysis (GPA) and extended Kalman filter (EKF). In this paper, the main health parameter degradations namely efficiency and flow capacity of the compressor and turbine sections are estimated and the responsible physical faults such as fouling and erosion are found. Two approaches are tested: The single-operating point and the multi-operating point. Simulation results show good estimations for diagnosis of most of the important degradations in the compressor and turbine sections for the single-point and improved estimations for the multi-point approach. | 2010 |
| Neural network model-based predictive control for multivariable nonlinear systems | Bahareh Vatankhah Alamdari, Alireza Fatehi, Ali Khaki-Sedigh | A nonlinear model predictive control (NMPC) algorithm based on a neural network model is proposed for multivariable nonlinear systems. A multi-input multi-output model is developed using multilayer perceptron (MLP) neural network which is trained by Levenberg-Marquardt algorithm and amplitude modulated pseudo random binary (APRBS) signals with noise as data sets. Model predictive control also uses Levenberg-Marquardt algorithm for the control signal optimization. The control performance is improved by using a disturbance model that compensates both model mismatch and external disturbance. The learning rate of disturbance estimation network changes adaptively to treat the model mismatch differently from the external disturbance. Simulation results using the quadruple-tank are employed to show the effectiveness of the method. | 2010 |
| Robust control of a pH neutralization process plant using QFT | R Shabani, A Khaki Sedigh, K Salahshoor | Inherent pH process nonlinearity and time-varying characteristics impose a highly challenging control problem. This paper presents an incorporation of offline process model identification and a QFT control methodology to develop a robust control scheme for a pH neutralization process plant on the basis of SISO QFT bounds. The obtained simulation results indicate the efficiency of the proposed control scheme to accomplish both the regulatory and servo tracking objectives. | 2010 |
| An analysis of variance approach to tuning of generalized predictive controllers for second order plus dead time models | Amir Reza Neshasteriz, Ali Khaki-Sedigh, Houman Sadjadian | This paper presents a new tuning strategy for Generalized Predictive Controllers (GPC) based on Analysis of Variance (ANOVA). This strategy is derived for Second Order plus Dead Time (SOPDT) models of an industrial plant. Moreover, SOPDT modeling allows oscillating modes to be included in the model dynamics. The tuning strategy employs a simple expression for the tuning parameter as a function of plant parameters which is absent in earlier tuning attempts. This novel expression is extracted using ANOVA method combined with nonlinear regression. Also, a better performance index value and more convenient implementation are obtained in comparison with the conventional GPC tuning methods. Therefore, the tuning strategy for SOPDT models is both more comprehensive and more effective than traditional First Order plus Dead Time (FOPDT) model tunings. The proposed strategy is verified by two … | 2010 |
| An ANOVA based analytical dynamic matrix controller tuning procedure for FOPDT models | Peyman Bagheri, Ali Khaki-Sedigh | Dynamic Matrix Control (DMC) is a widely used model predictive controller (MPC) in industrial plants. The successful implementation of DMC in practical applications requires a proper tuning of the controller. The available tuning procedures are mainly based on experience and empirical results. This paper develops an analytical tool for DMC tuning. It is based on the application of Analysis of Variance (ANOVA) and nonlinear regression analysis for First Order plus Dead Time (FOPDT) process models. It leads to a simple formula which involves the model parameters. The proposed method is validated via simulations as well as experimental results. A nonlinear pH neutralization model is used for the simulation studied. It is further implemented on a laboratory scale control level plant. A robustness analysis is performed based on the simulation results. Finally, comparison results are provided to show the effectiveness of the proposed methodology. | 2010 |
| Design of supervisory based switching QFT controllers for improved closed loop performance | Omid Namaki-Shoushtari, A Khaki Sedigh | In this paper, the problem of supervisory based switching Quantitative Feedback Theory (QFT) control is proposed for the control of highly uncertain plants. According to this strategy, the uncertainty region is divided into smaller regions with a nominal model. It is assumed that a QFT controller exits for robust stability and performance of the individual uncertain sets. The proposed control architecture is made up by these local controllers, which commute among themselves in accordance with the decision of a high level decision maker called the supervisor. The supervisor makes the decision by comparing the candidate local model behavior with the one of the plant and selects the controller corresponding to the best fitted model. A hysteresis switching logic is used to slow down switching for stability reasons. It is shown that this strategy leads to improved closed loop performance, and can also handle the uncertainty … | 2010 |
| Multilinear modeling and identification of the V94. 2 gas turbine for control system design purposes | Zoliekha Abdollahi, Maryam Hantehzadeh, Ali Khaki Sedigh, Hiwa Khaledi | Gas turbines are used widely in power generation, oil and gas industries, process plants and aviation. Efficiency and reliability is crucial in such applications. Hence, accurate modeling and control system designing is necessary. This paper first presents a nonlinear modeling of a single-shaft gas turbine in power generation application. This model is developed by solving differential and algebraic thermo dynamic equations and using turbine’s component maps. Using this complex model, a number of linear models is identified around turbine’s operating points. Effect of frequency and ambient condition is also considered in the models. Comparing these models, reduced number of linear models is selected to cover turbine’s entire operating range. These models are validated using further identification tests and nonlinear model responses. | 2010 |
| Traffic state variables estimating and predicting with extended Kalman filtering | Javad Abdi, Behzad Moshiri, Ehsan Jafari, A Khaki Sedigh | To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of traffic systems. METANET model is one of the most applicable models in traffic modeling which parameters have plenty of effects on model behavior. In this paper, we describe the effects of the model parameters on the model behavior and the estimation quality of system states in the case of undetermined parameters. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic traffic networks for preparing proper signal in traffic control. | 2010 |
| Optimal control of ride comfort of a passenger car: comparison between the hydro active and the fully active suspension systems | Ehsan Sarshari, Ali Khaki Sedigh, Hossein Sadati | In this research, a semi active control system with continuous variations along with hydro active dampers and springs is developed for a passenger car. The improvement of dynamic behavior of a passenger car with regard to weight constraint, energy consumption and cost highlights the need for the employment of such a semi active suspension system. Here, a full car model with hydro active subsystems including roll, pitch, bounce movements, and one degree of freedom for the driver is extracted, unlike the previous research in which merely the bouncing motion has been taken into account. By using the linearized car model equipped with the proposed hydro active system, the optimal damping force based on full state feedback control and LQR method is obtained for the improvement of the ride comfort and stability. In addition, practical constraints on manufacturing of the components and delay in the control … | 2010 |
| A modified proportional navigation guidance for accurate target hitting | A Moharampour, J Poshtan, A Khaki Sedigh | When a detector sensitive to the target plume IR seeker is used for tracking airborne targets, the seeker tends to follow the target hot point which is a point farther away from the target exhaust and its fuselage. In order to increase the missile effectiveness, it is necessary to modify the guidance law by adding a lead bias command. The resulting guidance is known as target adaptive guidance (TAG). First, the pure proportional navigation guidance (PPNG) in 3-dimensional state is explained in a new point of view. The main idea is based on the distinction between angular rate vector and rotation vector conceptions. The current innovation is based on selection of line of sight (LOS) coordinates. A comparison between two available choices for LOS coordinates system is proposed. An improvement is made by adding two additional terms. First term includes a cross range compensator which is used to provide and enhance path observability, and obtain convergent estimates of state variables. The second term is new concept lead bias term, which has been calculated by assuming an equivalent acceleration along the target longitudinal axis. Simulation results indicate that the lead bias term properly provides terminal conditions for accurate target interception. | 2010 |
| Flight control of a launch vehicle using an | M Zareh, M Rezaei, J Roshanian, A Khaki-Sedigh | This paper investigates the use of an | 2010 |
| Traffic state variables estimating and predicting with neural network via extended Kalman filter algorithm with estimated parameters as offline | Javad Abdi, Behzad Moshiri, Ehsan Jafari, A Khaki Sedigh | Developing mathematical models and estimating their parameters are fundamental issues for studying dynamic behaviors of traffic systems. METANET model is one of the most applicable models in traffic modeling in which the parameters have plenty of effects on the model behavior. In this paper, the effects of the model parameters on the model behavior and the estimation quality of the system states in the undetermined parameters are described. The extended Kalman filtering (EKF) algorithm instead of the error back-propagation (BP) algorithm is used to train artificial neural networks (ANNs) for dynamical traffic networks modeling. The basic idea is to prevent over fitting discrepancy occurrence caused by outliers in the training samples by the EKF. Numerical simulations show that the EKF algorithm is greater to the BP algorithm. | 2010 |
| Input-output pairing based on the control performance assessment index | S Choobkar, A Khaki Sedigh, A Fatehi | In this paper, the relation between Input-output pairing and minimum variance (MV) index as a performance index is studied. Control structure selection or the input-output pairing problem is a key step in designing decentralized controllers for multivariable. The Relative Gain Array (RGA) is an important tool for the control structure selection procedure. In this study, RGA is calculated and decentralized minimum variance controllers are designed for each feasible pairing. The MV performance index will be calculated from the closed loop transfer function using the markov parameters. It is shown that the value of the MV index can propose an input-output pairing that leads to minimum output variance. Several simulation results are provided to show the main points of the paper. | 2010 |
| Adaptive control of chaos in cardiac arrhythmia | SAMAREH ATTARSHARGHI, MOHAMMAD REZA JAHED-MOTLAGH, NASTARAN VASEGH, ALI KHAKI-SEDIGH | In this paper, logistic map is offered as a model for cardiac arrhythmia. In order to control cardiac chaos, a controller based on Delayed Feedback Control methodology is presented. This controller imposes the desired fixed-points on the map via an adaptive control law. Simulation results are provided to show the effectiveness of the proposed method. Finally advantages of the controller are mentioned. | 2010 |
| Multi-objective switching control via LMI optimization | Laven Soltanian, A Khaki Sedigh, Omid Namaki-Shoushtari | Multi-objective design problem is the optimization of various and often conflicting objectives for a complex system. In this paper, optimization is performed using Linear Matrix Inequalities (LMI’s). A switching strategy is proposed in order to improve the multi-objective control performance. Each controller design is based on a set of performance specifications. Instead of considering all the specifications defined by respective LMI sets simultaneously, only relevant objectives are included in the control design procedure. Then, switching is performed to meet multiple objectives. Assurance of the overall stability of the closed-loop is acknowledged via specific controller realization. Multi-objective designs are prone to conservatism, which is greatly reduced by the switching approach. The efficiency of the proposed methodology is illustrated through an example. | 2010 |
| Path Planning for Two-Link Navigation in an Unknown Environment using webcam | Shahed Shojaeipour, Ali Khaki Sedigh, Ali Shojaeipour, Edmund Ng Giap Weng, Nooshin Hadavi | In this article, we used image processing by a webcam connected on top of the arm robot. The robot navigation is in an unknown environment. Then start point and target point were determined for the robot, so the robot needs to have a program for path planning using Voronoi diagrams to find the path. After the possible path for moving the robot was found, the route information obtained was sent to the arm robot. The arm robot moves in the workspace and any time new information was processed via the webcam. The program was written using MATLAB software which at controls the robot’s movement the unknown environment. | 2010 |
| A fault-tolerant control technique for accommodation of partial actuator faults | Behnam Allahverdi Charandabi, Ali Khaki Sedigh, Farzad R Salmasi | In this paper, a robust adaptive controller for accommodation of partial actuator faults is introduced. The proposed controller is based on the robust adaptive model-reference control scheme with improved dead zone modification. The common problem of steady state error in robust adaptive systems with simple dead zone modification is resolved by tuning a specific parameter inside the dead zone with a different adaptive law. Different types of actuator faults including output offset, loss of efficiency, and output delay are compensated with the proposed method. We behave these faults as uncertainties and disturbances. The proposed technique does not need an extra unit for fault detection and diagnosis. Comparative simulation studies are performed to illustrate the effectiveness of the proposed control technique versus the robust adaptive controller with simple dead zone modification. | 2010 |
| COMPARATIVE STUDIES OF THE LMS AND MSLMS ALGORITHMS CONVERGENCE SPEED IN THE ACTIVE NOISE CONTROL SYSTEMS | ASHRAF ANVARI, MOHAMMAD HASAN SHENASA, SEDIGH ALI KHAKI | In this paper convergence speed of Least Mean Square (LMS) and Multi Stage Least Mean Square (MSLMS) in the active noise control systems have been studied and compared. The results show that MSLMS algorithm convergence rate is more efficient than LMS algorithm. Moreover; using of the above algorithms in the active noise control systems have been simulated. The simulation results show capability of the MLSM algorithm utilization in the active noise control systems. | 2010 |
| Optimal control of a nonlinear fed-batch fermentation process using model predictive approach | Ahmad Ashoori, Behzad Moshiri, Ali Khaki-Sedigh, Mohammad Reza Bakhtiari | Bioprocesses are involved in producing different pharmaceutical products. Complicated dynamics, nonlinearity and non-stationarity make controlling them a very delicate task. The main control goal is to get a pure product with a high concentration, which commonly is achieved by regulating temperature or pH at certain levels. This paper discusses model predictive control (MPC) based on a detailed unstructured model for penicillin production in a fed-batch fermentor. The novel approach used here is to use the inverse of penicillin concentration as a cost function instead of a common quadratic regulating one in an optimization block. The result of applying the obtained controller has been displayed and compared with the results of an auto-tuned PID controller used in previous works. Moreover, to avoid high computational cost, the nonlinear model is substituted with neuro-fuzzy piecewise linear models obtained … | 2009 |
| Identification using ANFIS with intelligent hybrid stable learning algorithm approaches and stability analysis of training methods | Mahdi Aliyari Shoorehdeli, Mohammad Teshnehlab, Ali Khaki Sedigh, M Ahmadieh Khanesar | This paper proposes a novel hybrid learning algorithm with stable learning laws for Adaptive Network based Fuzzy Inference System (ANFIS) as a system identifier and studies the stability of this algorithm. The new hybrid learning algorithm is based on particle swarm optimization (PSO) for training the antecedent part and forgetting factor recursive least square (FFRLS) for training the conclusion part. Two famous training algorithms for ANFIS are the gradient descent (GD) to update antecedent part parameters and using GD or recursive least square (RLS) to update conclusion part parameters. Lyapunov stability theory is used to study the stability of the proposed algorithms. This paper, also studies the stability of PSO as an optimizer in training the identifier. Stable learning algorithms for the antecedent and consequent parts of fuzzy rules are proposed. Some constraints are obtained and simulation results are given … | 2009 |
| Control Configuration Selection of Nonlinear Multivariable Plants | Ali Khaki-Sedigh, Bijan Moaveni, Ali Khaki-Sedigh, Bijan Moaveni | Introduction In spite of the extensive research of the previous decades in the field of input-output pairing for linear multivariable plants, the input-output pairing problem of nonlinear multivariable plants has received little attention. There are two main approaches to input-output pairing selection of nonlinear multivariable plants. The first and the most widely used approach is to employ the well established linear techniques for the linearized plant model. The second approach, which is the subject of the present chapter, directly uses the nonlinear plant model and derives the appropriate input-output pair either from direct nonlinear input-output relationship or from the nonlinear extensions of the linear concepts by introducing the nonlinear RGA. The materials of this chapter are based on (Daoutidis and Kravaris 1992), (Glad 1999) and (Moaveni and Khaki-Sedigh 2007) and covers the class of affine nonlinear … | 2009 |
| Training ANFIS as an identifier with intelligent hybrid stable learning algorithm based on particle swarm optimization and extended Kalman filter | Mahdi Aliyari Shoorehdeli, Mohammad Teshnehlab, Ali Khaki Sedigh | This paper proposes a novel hybrid learning algorithm with stable learning laws for Adaptive Network-based Fuzzy Inference System (ANFIS) as a system identifier. The proposed hybrid learning algorithm is based on the particle swarm optimization (PSO) for training the antecedent part and the extended Kalman filter (EKF) for training the conclusion part. Lyapunov stability theory is used to study the stability of the proposed algorithm. Comparison results of the proposed approach, PSO algorithm for training the antecedent part and recursive least squares (RLSs) or EKF algorithm for training the conclusion part, with the other classical approaches such as, gradient descent, resilient propagation, quick propagation, Levenberg–Marquardt for training the antecedent part and RLSs algorithm for training the conclusion part are provided. Moreover, it is shown that applying PSO, a powerful optimizer, to optimally train the … | 2009 |
| Adaptive vehicle lateral-plane motion control using optimal tire friction forces with saturation limits consideration | Javad Ahmadi, Ali Khaki Sedigh, Mansour Kabganian | This paper presents an adaptive nonlinear control scheme aimed at the improvement of the handling properties of vehicles. The control inputs for steering intervention are the steering angle and wheel torque for each wheel, i.e., two control inputs for each wheel. The control laws are obtained from a nonlinear 7-degree-of-freedom (DOF) vehicle model. A main loop and eight cascade loops are the basic components of the integrated control system. In the main loop, tire friction forces are manipulated with the aim of canceling the nonlinearities in a way that the error dynamics of the feedback linearized system has sufficient degrees of exponential stability; meanwhile, the saturation limits of tires and the bandwidth of the actuators in the inner loops are taken into account. A modified inverse tire model is constructed to transform the desired tire friction forces to the desired wheel slip and sideslip angle. In the next step … | 2009 |
| Identification using ANFIS with intelligent hybrid stable learning algorithm approaches | Mahdi Aliyari Shoorehdeli, Mohammad Teshnehlab, Ali Khaki Sedigh | This paper suggests novel hybrid learning algorithm with stable learning laws for adaptive network based fuzzy inference system (ANFIS) as a system identifier and studies the stability of this algorithm. The new hybrid learning algorithm is based on particle swarm optimization (PSO) for training the antecedent part and gradient descent (GD) for training the conclusion part. Lyapunov stability theory is used to study the stability of the proposed algorithm. This paper, studies the stability of PSO as an optimizer in training the identifier, for the first time. Stable learning algorithms for the antecedent and consequent parts of fuzzy rules are proposed. Some constraints are obtained and simulation results are given to validate the results. It is shown that instability will not occur for the leaning rate and PSO factors in the presence of constraints. The learning rate can be calculated on-line and will provide an adaptive … | 2009 |
| Input− output pairing using effective relative energy array | N Monshizadeh-Naini, A Fatehi, A Khaki-Sedigh | This paper provides an extended pairing criterion based on the effective relative gain array. The extension is achieved in two steps. First, an energy based compromise between steady state gain and bandwidth information of the plant is proposed. Then, it is argued that the best pairing may depend on the closed-loop specifications. Thus, to make this extension practical and precise, a simple solution to take into account the bandwidth of the desired closed-loop plant is introduced. To show the effectiveness of the proposed method, several examples are discussed. These examples include the cases where the conventional ERGA leads to an appropriate result and is in agreement with the proposed pairing criterion. They also include the cases where the original ERGA leads to an improper pairing while the proposed method achieves the acceptable pairs. | 2009 |
| Chaos control in delayed chaotic systems via sliding mode based delayed feedback | Nastaran Vasegh, Ali Khaki Sedigh | This paper investigates chaos control for scalar delayed chaotic systems using sliding mode control strategy. Sliding surface design is based on delayed feedback controller. It is shown that the proposed controller can achieve stability for an arbitrary unstable fixed point (UPF) or unstable periodic orbit (UPO) with arbitrary period. The chaotic system used in this study to illustrate the theoretical concepts is the well known Mackey–Glass model. Simulation results show the effectiveness of the designed nonlinear sliding mode controller. | 2009 |
| Adaptive control of nonlinear in parameters chaotic system via Lyapunov exponents placement | Moosa Ayati, Ali Khaki-Sedigh | This paper proposes a new method for the adaptive control of nonlinear in parameters (NLP) chaotic systems. A method based on Lagrangian of a cost function is used to identify the parameters of the system. Estimation results are used to calculate the Lyapunov exponents adaptively. Finally, the Lyapunov exponents placement method is used to assign the desired Lyapunov exponents of the closed loop system. | 2009 |
| Chaos control via TDFC in time-delayed systems: The harmonic balance approach | Nastaran Vasegh, Ali Khaki Sedigh | This Letter deals with the problem of designing time-delayed feedback controllers (TDFCs) to stabilize unstable equilibrium points and periodic orbits for a class of continuous time-delayed chaotic systems. Harmonic balance approach is used to select the appropriate controller parameters: delay time and feedback gain. The established theoretical results are illustrated via a case study of the well-known Logistic model. | 2009 |
| Observer-based adaptive control of chaos in nonlinear discrete-time systems using time-delayed state feedback | Amin Yazdanpanah Goharrizi, Ali Khaki-Sedigh, Nariman Sepehri | A new approach to adaptive control of chaos in a class of nonlinear discrete-time-varying systems, using a delayed state feedback scheme, is presented. It is discussed that such systems can show chaotic behavior as their parameters change. A strategy is employed for on-line calculation of the Lyapunov exponents that will be used within an adaptive scheme that decides on the control effort to suppress the chaotic behavior once detected. The scheme is further augmented with a nonlinear observer for estimation of the states that are required by the controller but are hard to measure. Simulation results for chaotic control problem of Jin map are provided to show the effectiveness of the proposed scheme. | 2009 |
| Simultaneous estimation of two bending vibration frequencies for attitude control of a flexible launch vehicle | AM Khoshnood, J Roshanian, AA Jafari, A Khaki-Sedigh | Current developments in the aerospace flight devices have led to a control system being designed in the presence of elastic behaviour. However, there are several ways to reduce the destructive effects of vibration in flexible systems. In this paper, a practical approach called ‘rigid model reference’ is extended to two vibration modes based on the gradient method. Furthermore, the existence of two dominant bending vibration modes in the output of measurement devices leads to a redesign of the control system. Robust stability of the new algorithm is investigated by using Kharitonov theorem. Simulation results illustrate considerable reduction of vibration effects on the output of measurement system considering the first and the second bending vibration modes. | 2009 |
| Design of decentralized supervisory based switching QFT controller for uncertain multivariable plants | Omid Namaki-Shoushtari, A Khaki Sedigh | In this paper, design of decentralized switching control for uncertain multivariable plants based on the Quantitative Feedback Theory (QFT) is considered. In the proposed strategy, the uncertainty region is divided into smaller regions with a nominal model. It is assumed that a MIMO-QFT controller exists for robust stability and performance of the individual uncertain sets. The proposed control structure is made up by these local controllers, which commute among themselves in accordance with the decision of a high level decision maker called the supervisor. The supervisor makes the decision by comparing the local models behaviors with the one of the plant and selects the controller corresponding to the best fitted model. A hysteresis switching logic is used to slow down switching to guarantee the overall closed loop stability. It is shown that this strategy provides a stable and robust adaptive controller to deal with … | 2009 |
| Enhancement of multi-objective control performance via switching | Laven Soltanian, Ali Khaki Sedigh, Omid Namaki-Shoushtari | Control system design for a complex system encompasses the optimization of different and often conflicting objectives leading to a multiple objective design problem. In this paper, a switching strategy is proposed to solve the multiple objective controller design. Each controller is designed based on a set of performance specifications. Control realization considerations are used to ensure overall closed loop stability. Linear matrix inequalities are employed in the controller design process. Multi objective designs are always prone to over conservatism, which is greatly reduced by the switching strategy. Simulation results are used to show the effectiveness of the design methodology. | 2009 |
| The Effect of Tuning in Multiple-Model Adaptive Controllers: A Case Study | Ehsan Peymani, Alireza Fatehi, Ali Khaki Sedigh | In this paper, two types of multiple-model adaptive controllers are practically evaluated on a laboratory-scale pH neutralization process. The first one is supervisory switching multiple-model adaptive controller (SMMAC) whose model bank is fixed and selected a priori, and another one is a controller based on multiple models, switching, and tuning strategy (MMST) which uses the possibility of model bank tuning. In addition to investigation of the effect of tuning, the advantage of a disturbance rejection supervisor is studied. Various experiments and exhaustive numerical analyses are provided to assess the abilities of the proposed algorithms. | 2009 |
| Multi-objective control of an active vibration system via switching | L Soltanian, A Khaki Sedigh, O Namaki-Shoushtari | Multi-objective control is the problem of optimising various conflicting objectives. In this paper, the multi-objective active vibration control via switching is proposed. The switching is applied to the separately designed H 2 and H w controllers, instead of considering both objectives in the synthesis of a single controller. Each controller is designed using linear matrix inequalities (LMIs). The overall stability of the closed-loop is guaranteed through a specific controller realisation. The H 2 controller is utilised to improve the transient response and the H ¿ controller in steady-state performance. The switching approach in multi-objective control reduces the conservatism of the design. Control of the active vibration system as a regulator is studied in the present paper. | 2009 |
| Stability Proof of Gain-Scheduling Controller for Skid-to-Turn Missile Using Kharitonov Theorem | MA Sharbafi, A Mohammadinejad Mohammadinejad, Jafar Roshanian, A Kh Sedigh | Gain scheduling is one of the most popular nonlinear control design approaches which has been widely and successfully applied in fields ranging from aerospace to process control. Despite the wide application of gain scheduling controllers, there is a notable lack of analysis on the stability of these controllers. The most common application of these kinds of controllers is in the field of flight control and autopilots. The main goal of this paper is to apply a methodology to prove stability of a gain scheduled controller used in directing Skid-to-Turn missiles. One of the most widespread applications of gain scheduling controller is the main problem of this paper. To design the controller we use pole placement in state feedback controllers and a kind of innovative interpolation to reduce jumping in gains related to changing the flight conditions. Finally we utilize root locus and Kharitonov’s Theorem to prove stability of the … | 2009 |
| RANGE ESTIMATION FOR IR HOMING MISSILES | A Moharampour, J Poshtan, SEDIGH A KHAKI | In this paper, pure proportional guidance in 3-D space is first explained with a new perception. The main idea is based upon the distinction between angular rate vector and rotation vector conceptions. In this innovation, the emphasis is based upon the selection of line of sight coordinates and comparison between the two available views for choosing this system. Then, using an additional term, an improvement to this law is made. This term compromises a cross range compensator, which is used to provide first fluctuations for obtaining convergent estimates of state variables. Then, a state-space description within the improved spherical coordinate system has been offered. The available measurements in this system have been chosen with regard to the considered practical points. Then, the issue of range-to-target estimation is proposed and some non-linear filters, such as extended Kalman filter, unscented Kalman filter, particle filter, EKF particle filter, and UKF particle filter in the modified spherical coordinates have been used. Simulations indicate that the proposed tracking filters in conjunction with the dual guidance law are able to provide the convergence of the range estimation for both maneuvering and non-maneuvering targets. | 2009 |
| Advanced Control Systems: Analysis and Design | K Sedigh | • Frequency domain, and s-Plane Design methodologies initiated in the 30’s and 40’s• The Nyquist–Bode–Nichols Approach• The Root Locus Method Introduced by Evans• PID Control | 2009 |
| PH control of penicillin fermentation process using predictive approach | A Ashoori, B Moshiri, A Ramezani, M Reza Bakhtiari, A Khaki-Sedigh | Bioprocesses which are involved in producing different pharmaceutical products may conveniently be classified according to the mode chosen for the process: either batch, fed-batch or continuous. From the control engineer’s viewpoint they are fed-batch processes, which present the greatest challenge to get a pure product with a high concentration. Complicated dynamics, nonlinearity and non-stationarity make controlling them a very delicate task. pH control of bioreactors has been an interesting problem from both implementation and controller design points of view. This is particularly true if the complex microbial interactions yield significant nonlinear behavior. When this occurs, conventional control strategies may not succeed and more advanced strategies need to be suggested. This paper discusses model predictive control (MPC) based on a detailed unstructured model for penicillin production in a fed-batch fermentor. The approach used here is to use quadratic cost function for pH regulation, while taking into account control signal fluctuations in the optimization block. The result of applying the obtained controller and also its sensitivity to disturbance have been displayed and compared with the results of an auto-tuned PID controller used in previous works. The merit of this method is its low computational cost of solving the optimization problem, while leading to a closed form controller as well. | 2009 |
| Generalized Predictive Control of a Multivariable pH Neutralization Process using Independent Model Approach | Peyman Bagheri, Ali Khaki-Sedigh, Amirreza Neshastehriz | Independent model approach (GPCI) is an effective method to solve the control problem of uncertain nonlinear systems due to its insensitivity to model uncertainties. Thus, due to the robustness of GPCI, one model instead of multi-model methods can be sufficient. Extreme nonlinearity and exhibition of severe interaction effects of multivariable pH processes makes it an appropriate test bed for evaluation of advanced controllers such as GPCI. In this paper, GPCI strategy is applied to this process and the simulation results demonstrate the effectiveness and validity of the method. | 2009 |
| Design and implementation of multi IMC-PID for a pressure plant | Faezeh Yeganli, Niusha Eshghi, S Faegheh Yeganli, Ali Khaki Sedigh | This paper studies Internal Model Control (IMC) and its structure and applications in process. By using the capability of IMC we obtained PID coefficients and designed the IMC-PID controller. Then the IMC-PID is used in multi controller structure to control the pressure plant (RT532). | 2009 |
| POWER SYSTEM STABILITY IMPROVEMENT USING QFT-BASED EXCITATION ROBUST CONTROL | FOROUD A AKBARI, HOSSEIN SEYFI, SEDIGH A KHAKI | Due to uncertainties in system modeling as well as system parameters, current excitation systems are unable to perform quite satisfactorily over a wide range of operating conditions. In this paper a QFT-based excitation robust control is proposed which the above mentioned uncertainties are, somehow, considered. The Horowitz second method is employed in the design of the nonlinear QFT controller. | 2009 |
| Control Configuration Selection of Linear Uncertain Multivariable Plants | Ali Khaki-Sedigh, Bijan Moaveni, Ali Khaki-Sedigh, Bijan Moaveni | Introduction Modeling of complex multivariable plants is always subject to uncertainty in their linear models. However, in the face of unknown or uncertain multivariable plants, the control configuration of the plant may endure fundamental changes, which will severely degrade the decentralized controller performance. The well-known input-output pairing techniques described in previous sections are unable to analyze the effect of uncertainty on input-output pairing and only recently, pairing methods are proposed for uncertain multivariable plants. The approaches to control configuration selection in the presence of uncertainty can be categorized in the following classes: Structured uncertainties. Diagonal input uncertainties. Condition number and robustness analysis. Statistical description … | 2009 |
| Control Configuration Selection of Linear Multivariable Plants Based on the State-Space Models | Ali Khaki-Sedigh, Bijan Moaveni, Ali Khaki-Sedigh, Bijan Moaveni | In the previous chapters, input-output pairing methods based on the transfer function model of the plant are introduced. The conventional RGA uses the steady state transfer function matrix, and the advanced pairing methods based on the RGA concept or the passivity approach use the dynamic transfer function matrix. In this chapter, input-output pairing methods based on the dynamical state-space model of the plant are introduced. State space is an internal description of the plant and it is therefore expected to support effective control structure methodologies. | 2009 |
| Mathematical Models Used in Examples | Ali Khaki-Sedigh, Bijan Moaveni, Ali Khaki-Sedigh, Bijan Moaveni | Distillation Column Transfer Function Matrices Wood and Berry distillation column transfer function matrix (Wood and Berry 1973) | 2009 |
| Control Configuration of Linear Multivariable Plants: Advanced RGA Based Techniques | Ali Khaki-Sedigh, Bijan Moaveni, Ali Khaki-Sedigh, Bijan Moaveni | The RGA introduced in chapter 2 provides a powerful tool for measuring control loop interaction and it is a well established pairing technique in the industry, with decades of successful applications. Although, the presented RGA analysis is sufficient for many practical problems, it is for some cases necessary to extend the RGA concept to handle certain shortcomings. This chapter provides an overview of the advanced pairing techniques based on the different RGA extensions. The presented methodologies are: The Dynamic Relative Gain Array. Dynamic relative gain is discussed in section 3.2.1. This is a dynamic extension of the RGA to improve the pairing capabilities of the steady state RGA in the cases where the RGA changes substantially with frequency and especially when the steady state RGA differs from the RGA at other key frequencies. In section 3.2.2, among the many different … | 2009 |
| Control Configuration Selection of Linear Multivariable Plants: The RGA Approach | Ali Khaki-Sedigh, Bijan Moaveni, Ali Khaki-Sedigh, Bijan Moaveni | The RGA was proposed by Bristol in 1966 to facilitate the design of decentralized control systems by determining the control system configurations with minimal interactions. | 2009 |
| Control Configuration Selection of Linear Multivariable Plants: SSV and Passivity Based Techniques | Ali Khaki-Sedigh, Bijan Moaveni, Ali Khaki-Sedigh, Bijan Moaveni | The advanced RGA based techniques introduced in chapter 3 provide powerful extensions to the well established RGA methodologies. Each of the proposed RGA extensions solves a problem not considered by the static classical RGA. This chapter considers two advanced approaches for control configuration selection that are not RGA based. These techniques are: SSV Approach to Input-Output Pairing. In this approach, Structured Singular Values (SSV) is employed to quantify the interaction in linear multivariable plants with diagonal or block diagonal controllers. Closed loop stability and performance under decentralized control corresponding to a selected control structure is also considered. The main ideas are given in section 4.2. Passivity based Approach to Control Configuration Selection. This recently developed approach is presented in section 4.3. This strategy … | 2009 |
| Model reference adaptive control for a flexible launch vehicle | A. Khoshnood, J. Roshanian, A. Khaki-Sedig | In the present paper, an adaptive control approach for a flexible launch vehicle is proposed. This approach makes use of gain scheduling and model reference adaptive filter methods to control the flexible behaviours of the launch vehicle structure, which can lead to control system stability degradation. Applying this adaptive controller to an eight-degrees-of-freedom flexible launch vehicle, gives stable and desired responses. Because the designed adaptive controller adjusts only one single parameter and is designed based on the MIT (Massachusetts Institute of Technology) rule, it is simpler and faster than the other approaches. Therefore, this newly designed algorithm is less central processing unit-intensive, which makes it easier to implement in real-time applications. | 2008 |
| Input–output pairing analysis for uncertain multivariable processes | Bijan Moaveni, Ali Khaki Sedigh | Decentralized control structure is widely employed in many industrial multivariable processes. In this approach, control structure design and in particular input–output pairing is a vital stage in the design procedure. There are several powerful methods to select the appropriate input–output pair in linear multivariable plants. However, in the face of plant uncertainties, the input–output pairs can change. Input–output pairing problem, in the presence of uncertainties, and its consequences on the pairing problem have not been widely addressed. In this paper, Hankel interaction index array is used to choose the appropriate input–output pair and a new method is proposed to compute Hankel interaction index array, which reduces the computational load. Also, a theorem will be presented to show the effect of additive uncertainties on input–output pairing of the process. An upper bound on the element variations of Hankel … | 2008 |
| Delayed feedback control of time-delayed chaotic systems: Analytical approach at Hopf bifurcation | Nastaran Vasegh, Ali Khaki Sedigh | This Letter is concerned with bifurcation and chaos control in scalar delayed differential equations with delay parameter τ. By linear stability analysis, the conditions under which a sequence of Hopf bifurcation occurs at the equilibrium points are obtained. The delayed feedback controller is used to stabilize unstable periodic orbits. To find the controller delay, it is chosen such that the Hopf bifurcation remains unchanged. Also, the controller feedback gain is determined such that the corresponding unstable periodic orbit becomes stable. Numerical simulations are used to verify the analytical results. | 2008 |
| Novel hybrid learning algorithms for tuning ANFIS parameters as an identifier using fuzzy PSO | Mohammad Teshnehlab, M Aliyari Shoorehdeli, Ali Khaki Sedigh | This paper introduces a new hybrid approach for training the adaptive network based fuzzy inference system (ANFIS) and a new type of particle swarm optimizers (PSO). The previous works emphasized on gradient base method or least square (LS) based method. This study applied one of the swarm intelligent branches, PSO. The hybrid method composes fuzzy PSO with recursive least square (RLS) for training. We use PSO with some changes for training procedure parameters in antecedent part. These changes are inspired from fuzzy systems method and using fuzzy rules for tuning PSO parameters during training algorithms. The simulation results show that in comparison with current gradient based training, and authors previous hybrid method the proposed training have a good adaptation to complex plants and train less parameter than gradient base methods. | 2008 |
| Disturbance rejection in neural network model predictive control | Alireza Fatehi, Houman Sadjadian, Ali Khaki-Sedigh, Ali Jazayeri | Neural Network Model Predictive Control (NN-MPC) combines reliable prediction of neural network with excellent performance of model predictive control using nonlinear Levenberg-Marquardt optimization. It is shown that this structure is prone to steady-state error when external disturbances enter or actual system varies from its model. In this paper, these model uncertainties are taken into account using a disturbance model with iterative learning which adaptively change the learning rate to treat gradual effect of the model mismatch differently from the drastic changes of external disturbance. Then, a high-pass filter on error signal is designed to distinguish disturbances from model mismatches. Practical implementation results as well as simulation results demonstrate good performance of the proposed control method. | 2008 |
| Automatic learning in multiple model adaptive control | Ehsan Peymani, Alireza Fatehi, A Khaki Sedigh | Control based on multiple models (MM) is an effective strategy to cope with structural and parametric uncertainty of systems with highly nonlinear dynamics. It relies on a set of local models describing different operating modes of the system. Therefore, the performance is strongly depends on the distribution of the models in the defined operating space. In this paper, the problem of on-line construction of local model set is considered. The necessary specifications of an autonomous learning method are stated, and a high-level supervisor is designed to add an appropriate model to the available model set. The proposed algorithm is evaluated in a simulated pH neutralization process which is a highly nonlinear plant and composed of both abrupt and large continuous changes. The preference of the multiple-model approach with learning ability on a conventional adaptive controller is studied. | 2008 |
| An experimental comparison of adaptive controllers on a pH neutralization pilot plant | Ehsan Peymani, Alireza Fatehi, Pouya Bashivan, Ali Khaki Sedigh | Inherent nonlinearity of pH processes causes that they are recognized as an appropriate test bench for evaluation of advanced controllers. Because of special characteristics of them, it is evident that adaptive controllers outperform others. This paper presents a comparison between a conventional adaptive controller and a switching multiple-model adaptive one in both regulation and disturbance rejection points of view. A disturbance rejection supervisor is designed to improve the performance of the adaptive controllers in the presence of unmeasured disturbances. A laboratory scale pH process is used as an application example. | 2008 |
| Contractive predictive control of mixed logical dynamical hybrid systems | Jalal Habibi, Behzad Moshiri, Ali Khaki Sedigh | Current state-of-the-art approaches for control of hybrid systems face two main important challenging problems which are stabilization and computational complexity. This paper aims at improving a special strategy ie predictive control for a special class of hybrid systems ie mixed logical dynamical systems. For mixed logical dynamical systems as a main class of hybrid systems, the only existing way to ensure the closed loop stability of predictive controllers is to use a terminal state equality constraint in the successive optimization problems. Limitations caused by this type of constraint have been discussed. Contractive predictive control is proposed as a good alternative which assures the closed loop stability in a more feasible manner. As a Lyapunov function, the L1 norm of the state vector is enforced to shrink in successive optimization steps. A suboptimal version of contractive MPC scheme has been proposed … | 2008 |
| A new approach to compute the cross-Gramian matrix and its application in input-output pairing of linear multivariable plants | Bijan Moaveni, A Khaki-Sedigh | In this study, a new approach to solve the Sylvester equation, AX+ XA=-BC is derived. The calculated cross-Gramian matrix, which results from the Sylvester equation, proposes a new input-output pairing analysis for stable multivariable plants. This new approach is based on the cross-Gramian matrix of SISO elementary subsystems built from the original MIMO plant and the main advantage of the method is its simplicity to choose the best input-output pair, though, it considers the plant dynamic properties. | 2008 |
| Stable learning algorithm approaches for ANFIS as an identifier | M Aliyari Shoorehdeli, M Teshnehlab, AK Sedigh | This study suggests new learning laws for Adaptive Network based Fuzzy Inference System that is structured on the basis of TSK type III as a system identifier. Stable learning algorithms for consequence parts of TSK type III rules are proposed on the basis of the Lyapunov stability theory and some constraints are obtained. Simulation results are given to validate the results. It is shown that instability will not occur for learning rates in the presence of constraints. The learning rate can be calculated online from the input–output data, and an adaptive learning for the Adaptive Network based Fuzzy Inference System structure can be provided. | 2008 |
| Adaptive control of nonlinear in parameters chaotic systems | SM Ayati, A Khaki-Sedigh | This paper presents the adaptive control of chaotic systems, which are nonlinear in parameters (NLP). A method based on Lagrangian of an objective functional is used to identify the parameters of the system. Also this method is improved to result in better rate of convergence of the estimated parameters. Estimation results are used to calculate the Lyapunov exponents adaptively. Finally, the Lyapunov exponents placement method is used to assign the desired Lyapunov exponents of the closed loop system. Simulation results are provided to show the effectiveness of the results. | 2008 |
| A new method for active noise cancellation in the presence of three unknown moving sources | Mohammad Abdollahpouri, Ali Khaki-Sedigh, Hamid Khaloozadeh | This paper introduces a new scheme for building a clean room with no unwanted sound in it. Recent efforts for building such rooms always encounter problems because of the stochastic nature of these systems. A real clean room not only faces some non-moving sources, but also faces some moving ones, that probably the sound source is a moving one in reality. In order to solve the problem of motion of those moving sources, one must design a method to solve this problem which we definitely encounter with. Active noise cancellation needs the direction of transmission of the unwanted sound in order to reduce its effect. Hence, these rooms need an identifier, which we suggest a clean room identification algorithm in this paper. Recent efforts for building these kind of room, always suppose the non- moving sound sources which we may encounter a moving one in every day life. The other problem is the mutual effect … | 2008 |
| A Modified Proportional Navigation Guidance for Range Estimation | A Moharampour, J Poshtan, SEDIGH A KHAKI | In this paper, after defining pure proportional navigation guidance in the 3-dimensional state nom a new point of view, range estimation for passive homing missiles is explained. Modeling has been performed by using line of sight coordinates with a particular definition. To obtain convergent estimates of those state variables involved particularly in range channel and unavailable nom IR trackers, nonlinear filters such as sequential UD extended Kalman filter and Unscented Kalman filter in modified spherical coordinate combined with a modified proportional navigation guidance law are proposed. Simulation results indicate that the proposed tracking filters in conjunction with the dual guidance law are able to provide the convergence of the range estimate for both maneuvering and non-maneuvering targets. | 2008 |
| Designing Integral-Lead Compensator Based on Frequency Domain Response | Alireza Doodman Tipi, Ali Khaki Sedigh, Alireza Hadi | In this method, firstly, the frequency responses of system in a few points are predicted and are compared with the frequency response of the model reference that is the proper loop gain function. In the next step, a second order controller for compensating is designed. Finally, a benchmark for the convergence of the real loop to the reference function and the stability of the closed loop is introduced. As the convergence of the response is adequate in a limited band the structural information of the system such as order of the system, order and number of delays is not necessary. The application of this method is in control of high order system and the systems with delayed response. | 2008 |
| A disturbance rejection supervisor in multiple-model based control | Ehsan Peymani, Alireza Fatehi, Ali Khaki Sedigh | In this paper, a multiple models, switching, and tuning control algorithm based on poleplacement control is studied. Drawbacks of the algorithm in disturbance rejection are discussed, and a novel supervisor to enhance the decision-making procedure is developed. The modified algorithm is evaluated in a simulation study for a nonlinear pH neutralization process. Comparison results are provided to evaluate the performance and robustness characteristics of the proposed algorithm. | 2008 |
| Improved FODPT model estimation with Delayedrelay feedback for constant time dominant processes | ZT Yaman | In this paper with reference to analytical results of different well-known relay feedback methods, we illustrate a main deficiency in parameter estimation of processes with a small ratio of time delay to time constant. Then to rectify this problem we introduce a modified relay feedback structure with additional delay to estimate the parameters of the FOPDT transfer function of the system. The significance of this method lies in the fact that many industrial plants perform fairly such as FOPDT systems, and a wide range of processes have negligible dead time versus their long constant time. Also, the estimated FOPDT transfer function from proposed relay feedback test can be used as a priori knowledge in advanced control strategies which need a FOPDT model of the system. The method is straightforward and simulation results illustrate the effectiveness, and simplicity of the proposed method. | 2008 |
| Model predictive control of a nonlinear fed-batch fermentation process | Ahmad Ashoori, Amir Hosein Ghods, Ali Khaki-Sedigh, Mohammad Reza Bakhtiari | Bioprocesses, which are involved in producing different antibiotics and other pharmaceutical products, may be conveniently classified according to the mode chosen for the process: either batch, fed-batch or continuous. From the control engineer’s viewpoint it is the fed-batch processes, however, which present the greatest challenge to get a pure product with a high concentration. To achieve this goal, control of the following parameters has significant importance dealing with these processes: temperature, pH, dissolved oxygen (DO2). Bioprocesses have complicated dynamics. Hence, their control is a delicate task; Nonlinearity and non-stationarity, which make modeling and parameter estimation particularly difficult perturbs such processes. Moreover, the scarcity of on-line measurements of the component concentrations (essential substrates, biomass and products of interest) makes this task more sophisticated. In … | 2008 |
| Suboptimal control of hybrid systems using approximate multi-parametric MILP | Jalal Habibi, Ali Khaki Sedigh | As a way to reduce the on-line computational burden, explicit solution to the problem of optimal control for some classes of hybrid systems can be found by reformulating the problem as multi-parametric MILP problems. The main contribution of this paper is the introduction of an approximation algorithm for solving a general class of mp-MILP problems. The algorithm wisely selects those binary sequences which make important improvement in the objective function if considered. It is shown that considerable reduction in computational complexity could be achieved by introduction of adjustable level of suboptimality. So a family of suboptimal controllers would be obtained for which the level of error and complexity can be adjusted by a tuning parameter. Several important theoretical results about approximate solutions to the mp-MILP problem are presented. It is shown that no part of the parameter space is lost during … | 2008 |
| Integrated vs usual treatment model in first episode-psychosis among Iranian adolescents | J Alaghband-Rad, Z Shahrivar, J Mahmoudi-gharaei, V Sharifi, H Amini, Y Mottaghipour, M Jalali Roudsari, M Motlagh, F Moharari, F Mousavi, H Shahrokhi, A Sedigh, N Salesian, F Razmjoo | 2008 | |
| Short term prediction of air pollution using MLP, GAMMA, ANFIS, and mixed training methods based on PSO | SHOUREHDELI M ALIARI, M Teshnehlab, SEDIGH A KHAKI | In this study we predict air pollution data by using Multi Layer Percepteron, Time Delay Line, Gamma and ANFIS by gradient free learning methods. This paper, using real data for Arak city during Oct 2003, the following pollution parameters are analysed: Co (Carbon Monoxide), PM 10 (Particulate Matter). | 2008 |
| Relay feedback based monitoring and autotuning of processes with gain nonlinearity | Zeinab Tehrani Zamani, Behzad Moshiri, Alireza Fatehi, Ali Khaki Sedigh | Performance assessment and monitoring of control systems can be used to improve the performance of industrial processes. In this paper, a novel relay feedback based method for monitoring and automatic retuning of a class of proportional-integral (PI) controllers is proposed for the systems with gain nonlinearity. For performance assessment of the closed loop system, a time domain evaluation criteria based on the integral of the absolute value of the error (IAE) and the normalized pick of the error in setpoint (SP) changes are presented. Simulation results on the highly nonlinear pH process have shown the effectiveness and feasibility of this method. | 2008 |
| An Improved Method for Tracking a Single Target in Variable Cluttered Environments | Fatemeh Rahemi, Ali Khaki Sedigh, Alireza Fatehi, Farbod Razzazi | Tracking moving objects in variable cluttered environments is an active area of research. It is common to use some simplifying assumption in such environments to facilitate the design. In this paper a new method for simulating the completely non-Gaussian cluttered environments is presented. The method is based on using the variable variance of process noise as a description of variability in such environments. The key objective is to find an effective algorithm for tracking a single moving object in variable cluttered environments, with utilization of the presented method. The new methodology is presented in two steps. In the first step we compare the accuracy of estimators in tracking a moving object, and in the second step, the goal is to find the best algorithm for tracking a single moving target in variable cluttered environments. | 2008 |
| Eigenstructure Assignment for Four-Wheel Anti-lock Braking System Model | J Mashayekhi Fard, MA Nekoui, A Khaki Sedigh | Minimal Stopping Distance, Guaranteed Steering ability and Stability are the three most important proposes in Anti-lock Braking System(ABS)realm. The ABS system is nonlinear, time variant, multivariable and uncertain. Up to now several researches have been done on ABS control system, but nearly all of them are intricate and expensive. In this paper we exploit a multivariable technique in linear control to attack the problem, which is Designed Linear Control with Multivariable Technique. The Optimal Eigenstructure Assignment with Genetic Algorithm(GA) method is also applied. Simulation and comparison studies are used to show the effectiveness of the proposed methods. | 2008 |
| Passivity-Based Structured Model Predictive Control with Guaranteed Stability | Ghazal Montaseri, Mohammad Javad Yazdanpanah, Ali Khaki-Sedigh | In this paper, a model predictive control scheme for a class of nonlinear systems is presented. In the proposed algorithm, the new cost function for MPC is defined. This cost function is inspired by the structure of passivity-based control. By simple tuning of weighting matrices, the asymptotic stability is guaranteed. Moreover, a closed-form solution to the optimal control problem is calculated via representing the nonlinear system in the state-dependent coefficient form of the state-space model. This point is of great importance in online applications. To demonstrate its efficiency, the passivity-based structured MPC is applied to control a rotational motion of a rigid body. | 2008 |
| A QFT/EEAS Design of Multivariable Robust Adaptive Controllers | O Namaki-Shoushtari, A Khaki Sedigh, B Nadjar Araabi | This paper presents a robust adaptive control design methodology for multi-input multi-output (MIMO) plants based on Quantitative Feedback Theory (QFT) and Externally Excited Adaptive System (EEAS), both of which are the novel ideas of Horowitz. Self Oscillating Adaptive Systems (SOAS) are proposed to mainly overcome the problem of large gain variations, which is important in certain applications. To further improve the SOAS design, the idea of EEAS was developed. Finally, combined QFT and EEAS proposed a robust adaptive controller for SISO uncertain plants. However, due to the complex design nature of the proposed combined methodology and the difficulty of an optimal design, this line of Horowitz’s research was not followed further. In this paper, to overcome the above mentioned problems the design procedure is reformulated as a set of cost functions and constraints. Genetic Algorithms are then … | 2008 |
| Novel hybrid learning algorithms for tuning ANFIS parameters using adaptive weighted PSO | M Aliyari Shoorehdeli, Mohammad Teshnehlab, AK Sedigh | This paper introduces a new hybrid approach for training the adaptive network based fuzzy inference system (ANFIS). The previous works emphasized on gradient base method or least square (LS) based method. In this study we apply one of the swarm intelligent branches, named particle swarm optimization (PSO). The hybrid method composes PSO with recursive least square (RLS) for training. We use PSO with some changes for training procedure parameters in antecedent part. These changes are inspired from Genetic Algorithm (GA) method and using Adaptive Weighted for PSO. The simulation results show that in comparison with current gradient based training, the novel training can have a comparable adaptation to complex plants and train less parameter than gradient base methods. Also, the results show this new hybrid approach has less complexity than other gradient based methods. | 2007 |
| Input-output pairing for nonlinear multivariable systems | Bijan Moaveni, Ali Khaki-Sedigh | Input-Output Pairing for Nonlinear Multivariable Systems – NASA/ADS Now on home page ads icon ads Enable full ADS view NASA/ADS Input-Output Pairing for Nonlinear Multivariable Systems Moaveni, Bijan ; Khaki-Sedigh, Ali Abstract Publication: Journal of Applied Sciences Pub Date: December 2007 DOI: 10.3923/jas.2007.3492.3498 Bibcode: 2007JApSc…7.3492M full text sources Publisher | © The SAO/NASA Astrophysics Data System adshelp[at]cfa.harvard.edu The ADS is operated by the Smithsonian Astrophysical Observatory under NASA Cooperative Agreement NNX16AC86A NASA logo Smithsonian logo Resources About ADS ADS Help What’s New Careers@ADS Social @adsabs ADS Blog Project Switch to full ADS Is ADS down? (or is it just me…) Smithsonian Institution Smithsonian Privacy Notice Smithsonian Terms of Use Smithsonian Astrophysical Observatory NASA … | 2007 |
| Improved multivariable quantitative feedback design for tracking error specifications | SM Mahdi Alavi, A Khaki-Sedigh, B Labibi, MJ Hayes | An improved design procedure for multi-input/multi-output (MIMO) quantitative feedback theory (QFT) problems involving tracking error specifications (TESs) has been presented. Appropriate transformation of the MIMO system to a series of equivalent single-input/single-output (SISO) problems is presented that motivates an improved synthesis procedure using feedback compensator and pre-filter transfer function matrices (TFMs). The key features of the procedure are that, for each equivalent SISO problem, (i) interactions and the effects of uncertainty are treated as an output disturbance, and (ii) sufficient conditions can be determined that assure desired levels of robust performance within the bandwidth region at a transformation cost that can be computed a priori. This paper also considers how the individual elements of the pre-filter TFM can be designed for MIMO QFT problems with a reduced level of … | 2007 |
| Anxiety disorders in multiple sclerosis: significance of obsessive-compulsive disorder comorbidity | AMIR SHAABANI, MOGHADAM J ATARI, Leily Panaghi, A SEDIGH | BACKGROUND: Considering reports on the associations of symptoms of anxiety disorders with multiple sclerosis (MS), this study aimed to 1) further evaluate various anxiety disorders systematically presenting in patients with MS and 2) compare the results with a control group. METHODS: To assess anxiety disorders in patients with MS in a case-control study, 85 registered patients in the Iranian Multiple Sclerosis Society (IMSS) were randomly selected according to the inclusion criteria. A group of healthy individuals whose age and gender were matched with the case group were also selected. Both groups underwent a clinical interview based on DSM-IV diagnostic criteria. RESULTS: Frequency of diagnosis of all anxiety disorders in the two groups was 22.4% and 7.1%, respectively, indicating a statistically significant difference. Frequency of obsessive-compulsive disorder (OCD) was significantly higher in the case group (P< 0.05). Relation of university education with the diagnosis of generalized anxiety disorder was significant too (P< 0.05). CONCLUSIONS: OCD in patients with MS was more frequently observed than in the control group. | 2007 |
| Optimized data fusion in an intelligent integrated GPS/INS system using genetic algorithm | Ali Asadian, Behzad Moshiri, Ali Khaki Sedigh, Caro Lucas | Most integrated inertial navigation systems (INS) and global positioning systems (GPS) have been implemented using the Kalman filtering technique with its drawbacks related to the need for predefined INS error model and observability of at least four satellites. Most recently, a method using a hybrid-adaptive network based fuzzy inference system (ANFIS) has been proposed which is trained during the availability of GPS signal to map the error between the GPS and the INS. Then it will be used to predict the error of the INS position components during GPS signal blockage. This paper introduces a genetic optimization algorithm that is used to update the ANFIS parameters with respect to the INS/GPS error function used as the objective function to be minimized. The results demonstrate the advantages of the genetically optimized ANFIS for INS/GPS integration in comparison with conventional ANFIS specially in the cases of satellites’ outages. Coping with this problem plays an important role in assessment of the fusion approach in land navigation. | 2007 |
| Further Theoretical Results on “Relative Gain Array for Norm-Bounded Uncertain Systems” | Bijan Moaveni, Ali Khaki Sedigh | 3. Conclusion In this correspondence paper, a theorem is given based on the main results of Kariwala et al. 1 for input-output pairing analysis for uncertain multivariable systems. A method to compute the relative gains’ variation bound of RGA to inputoutput pairing analysis is provided. The results can decrease the computational load in large-scale uncertain systems, solve the sensitivity analysis problem, and propose the appropriate pair, when there is no sign change for relative gains. | 2007 |
| Reconfigurable controller design for linear multivariable plants | Bijan Moaveni, Ali Khaki-Sedigh | Decentralised control is widely used for the control of multivariable plants. Prior to the design of the decentralised controllers, input-output pairing is an important step in the design procedure. In the face of unknown, uncertain or time varying plant parameters, the input-output selection may endure fundamental changes, which will severely degrade the decentralised controller performance. This paper proposes a reconfigurable structure for the design of the decentralised controller based on the adaptive control strategies. Simulation results are provided to show the effectiveness of the proposed methodology. | 2007 |
| A new stabilizing control law with respect to a control Lyapunov function and construction of control Lyapunov function for particular nonaffine nonlinear systems | A Shahmansoorian, B Moshiri, A Khaki Sedigh, S Mohammadi | In this paper, a new stabilizing control law with respect to a control Lyapunov function (CLF) is presented. This control law is similar to the pointwise min-norm control law. This control law is designed to maximize the angle between the gradient of the control Lyapunov function and the time derivative of the state vector at the state trajectory, which is defined in what follows as the “pointwise maximum angle control law.” A comparison with the pointwise minnorm control law is provided. A criterion of the stability performance of control laws that are designed with respect to a CLF is presented. Also, by proposing the concept of the “eigen-angle” for real square nonsingular matrices, the stabilization of some nonaffine nonlinear systems, and the construction of a CLF for such systems are reduced to the construction of CLFs for affine nonlinear (linear) systems. Finally, simulation results are provided to show the … | 2007 |
| Simulation of bending vibration effects on attitude control of a flexible launch vehicle | Jafar Roshanian, Ali Khaki-Sedigh, Abdolmajid Khoshnood | Simulation of bending vibration effects on a two-stage launch vehicle and design of a new adaptive algorithm to reduce the flexible behaviours are discussed in this paper. The new adaptive algorithm uses recursive least square (RLS) method and two notch filters for decoupling rigid and flexible dynamic of the launch vehicle, estimating the bending frequency and reducing vibration effects. Applying this adaptive controller to the launch vehicle control system satisfied all design requirements. As the designed adaptive controller decouples rigid and flexible dynamics for estimating the bending frequency, it is simpler and faster than the other approaches and uses less CPU- capacity. The proposed approach validated by developing 6DoF nonlinear simulation software. | 2007 |
| Neural network using genetic algorithms(NN using GA) for solving systems of linear equations and findingthe inversion of a matrix. | Z Ghassabi, B Moaveni, A Khaki-Sedigh | In this paper, we propose a one-layered neural network that recovers its input variables by genetic algorithms to solve the systems of linear equations (or, equivalently, matrix inversion).First we described solving systems of linear equations (matrix inversion) by mentioned neural network. Then, experimental results arepresented to show the effectiveness of the approach. Finally, future avenue of this research is proposed. | 2007 |
| Finding the Inversion of a Square Matrix and Pseudo-inverse of a Non-square Matrix by Hebbian Learning Rule | Zeinab Ghassabi, Ali Khaki-Sedigh | In this paper, we discuss a neural network based on hebbian learning rule for finding the inverse of a matrix. First we described finding the inverse of a matrix by mentioned neural network. Finally, experimental results for square and non-square matrices are presented to show the effectiveness of the approach. Proposed method is also scalable for finding the inversion of large-scale matrices. | 2007 |
| A novel training algorithm in ANFIS structure | M Aliyari Shoorehdeli, M Teshnehlab, AK Sedigh | This paper introduces a new hybrid approach for training the adaptive network based fuzzy inference system (ANFIS). The previous works emphasized on gradient base method or least square (LS) based method. In this study we apply one of the swarm intelligent branches, named particle swarm optimization (PSO). The hybrid method composes PSO with gradient decent (GD) for training. We use PSO with some changes for training procedure parameters in antecedent part. These changes are inspired from genetic algorithm (GA) method. The simulation results show that in comparison with current GD training, the novel training can have a better adaptation to complex plants. Also, the results show this new hybrid approach optimizes ANFIS parameters faster and better parameters than gradient base method | 2006 |
| Design of a satellite attitude control simulator | M Nasirian, H Bolandi, Ali Khaki Sedigh, AR Khoogar | Today satellites have important role in all parts of human living. For satellite correct communication should track satellite and so satellite antenna or camera should track Earth station correctly. Both correct attitude control and attitude determination are two factors to tracking from satellite. By using attitude control simulator could simulate attitude of satellite in each point of orbit with each disturbance. In this paper design of a satellite simulator by different methods of control and determination is investigated and some results are presented. | 2006 |
| Robust model reference adaptive control of active suspension system | Narges Maleki, Ali Khaki Sedigh, Batool Labibi | This paper discusses the design of a cascade controller for active suspension systems, to improve ride quality. In order to do this, in the main loop, a model reference adaptive controller is designed to attenuate disturbances due to rough roads. An internal loop provides the required control force for the main controller. The closed loop system has desired robust stability and performance in the presence of uncertainty due to time varying parameters and nonlinear dynamics of the actuator. The simulation results show the effectiveness of the suggested method in increasing ride comfort and safety while constrains of suspension system maneuverability is also satisfied | 2006 |
| Observer-based design of set-point tracking adaptive controllers for nonlinear chaotic systems | A Khaki-Sedigh, A Yazdanpanah-Goharrizi | A gradient based approach for the design of set-point tracking adaptive controllers for nonlinear chaotic systems is presented. In this approach, Lyapunov exponents are used to select the controller gain. In the case of unknown or time varying chaotic plants, the Lyapunov exponents may vary during the plant operation. In this paper, an effective adaptive strategy is used for online identification of Lyapunov exponents and adaptive control of nonlinear chaotic plants. Also, a nonlinear observer for estimation of the states is proposed. Simulation results are provided to show the effectiveness of the proposed methodology. | 2006 |
| Input-output pairing based on cross-gramian matrix | B Moaveni, A Khaki-Sedigh | Decentralized control is a well established approach to the control of multivariable plants. In this approach, control structure design and in particular input-output pairing is a vital stage in the design procedure. There are several methods such as RGA, balanced-realization, Hankel-norm based and gramian based approach to select the appropriate input/output pairs in linear multivariable plants. In this paper, a new input-output pairing method for stable multivariable plants is proposed. This new approach is based upon the cross-gramian matrix of SISO elementary subsystems built from the original MIMO plant. The main advantages of the method are simplicity and proposing an overall measure to choose the best input output pairs | 2006 |
| Predictive control of earth station antenna with backlash compensation | I Mohammadzaman, A Khaki Sedigh, M Nasirian, MH Ferdowsi | In this paper, Generalized Predictive Control (GPC) algorithm is implemented to control an earth station antenna. Nonlinear term in motors caused by gearbox or other parts is modeled by a backlash block. Simulation results show the effectiveness of GPC method for robust control in the presence of backlash nonlinearity without a priori knowledge about upper and lower bounds of backlash. Also, adaptation mechanism as a self tuning predictive control is used to conquer environment changing. | 2006 |
| Predictive control of non-minimum phase motor with backlash in an earth station antenna | Iman Mohammadzaman, Ali Khaki Sedigh, Mehrzad Nasirian | In this paper, generalized predictive control (GPC) algorithm is implemented to control an Earth station antenna with a non-minimum phase motor. Nonlinear term in motors caused by gearbox or other parts is modeled by a backlash block. Simulation results show the effectiveness of GPC method for robust control in the presence of backlash nonlinearity without a priori knowledge about upper and lower bounds of backlash. Also, adaptation mechanism as a self tuning predictive control is used to conquer environment changing. | 2006 |
| Performance benefits of hybrid control design for switched linear systems | Jalal Habibi, Behzad Moshiri, Ali Khaki Sedigh | Hybrid systems theory as a growing field in control theory provides some contributions for traditional control problems. Control of switched linear systems as a member of these categories has well-known solutions like multiple model control. Multiple model controllers provide a global control action by interpolating the individually-designed controllers. Since the hybrid systems methods are usually more complicated than the conventional control schemes, it is of great importance to explain these potential superiorities. The goal of this paper is to explain potential benefits which could be achieved by using hybrid control methods. Predictive control – as a powerful strategy to deal with complicated dynamics – is selected as the design basis for hybrid controller and for a multiple model controller. An illustrative test bench problem is introduced to compare the behavior of two controllers. It has been shown that the hybrid … | 2006 |
| Modeling hybrid systems with MLD approach and analysis of the model size and complexity | H Mahboubi, B Moshiri, A Khaki Seddigh | Recently, a great amount of interest has been shown in the field of modeling and controlling hybrid systems. One of the efficient and common methods in this area utilizes the mixed logicaldynamical (MLD) systems in the modeling. In this method, the system constraints are transformed into mixed-integer inequalities by defining some logic statements. In this paper, a system containing three tanks is modeled as a nonlinear switched system by using the MLD framework. Then, regarding this three-tank modeling, an ntank system is modeled and number of binary and continuous auxiliary variables and also number of mixed-integer inequalities are obtained in terms of n. Thereafter, the system size and complexity due to increase in number of tanks are considered. It is concluded that as number of tanks increases, the system size and complexity increase exponentially which hampers control of the system. Thus, it seems necessary to find some appropriate techniques for decreasing number of variables. | 2006 |
| On-line input/output pairing for linear and nonlinear multivariable plants using neural network | B Moaveni, A Khaki-Sedigh | Decentralized Control is a well established approach to the control of multivariable plants. In this method, control structure design and in particular inputoutput selection is a vital stage in the design procedure. There are several powerful methods to select the appropriate input/output pairs in linear multivariable plants. However, there is no general procedure to select the appropriate input/output pairs for nonlinear multivariable plants and linear multivariable plants in the presence of uncertainties, despite the fact that most practical systems are nonlinear and uncertain. In this paper, a new on-line estimation for RGA matrix using neural network for nonlinear or uncertain linear multivariable plants is proposed. Copyright© 2002 USTARTH | 2006 |
| Solving systems of linear equations and finding the inversion of a matrix by neural network using genetic algorithms (NN using GA) | Z Ghassabi, B Moaveni, A Khaki-Sedigh | In this paper, we propose a one-layered neural network that recovers its input variables by genetic algorithms to solve the systems of linear equations (or, equivalently, matrix inversion). First we described solving systems of linear equations (matrix inversion) by mentioned neural network. Then, experimental results are presented to show the effectiveness of the approach. Finally, future avenue of this research is proposed. | 2006 |
| Complexity and size analysis of hybrid system modeling with mixed logical dynamical approach | Hamid Mahboubi, Jalal Habibi, Behzad Moshiri, Ali Khaki-Sedigh | Recently, a great amount of interest has been shown in the field of modeling and control of hybrid systems. One of the efficient methods in this area utilizes the mixed logical-dynamical (MLD) systems in the modeling. In this method, the system constraints are transformed into mixed-integer inequalities by defining some logic statements. In this paper, a system containing three tanks is modeled as a nonlinear switched system using the MLD framework. Regarding this three-tank modeling, an n-tank system is modeled and number of binary and continuous auxiliary variables and also number of mixed-integer inequalities are obtained in terms of n. Then, the system size and complexity due to increase in number of tanks are considered. It is concluded that as the number of tanks increases, the system size and complexity increase exponentially which hampers control of the system. Therefore, methods should be found … | 2006 |
| Predictive control of earth station antenna with friction compensation | Iman Mohammadzaman, Ali Khaki Sedigh, Mehrzad Nasirian | In this paper, generalized predictive control (GPC) algorithm is implemented to control an Earth station antenna. Nonlinear term in motors caused by coulomb friction is modeled by a dead zone block. Simulation results show the effectiveness of GPC method for robust control in the presence of dead zone nonlinearity without a priori knowledge about upper and lower bounds of dead zone | 2006 |
| Advanced HSVC tuning in multi-machine power systems for loadability improvements | A Akbari Foroud, H Seifi, A Khaki Sedigh | Advanced high side voltage control (HSVC) regulation presents an attractive proposition for power system control. By proper tuning of its parameters, it can improve the voltage profile of the system. In this paper, we show how it can also enhance the loadability of a multimachine system. The genetic algorithm (GA) is employed to tune the parameters. Two test systems, a 21 bus and the IEEE 118 bus, are used to check the capability of the proposed algorithm. | 2006 |
| Suboptimal contractive predictive control for a class of hybrid systems | Jalal Habibi, Behzad Moshiri, Ali Khaki Sedigh | Current state-of-the-art approaches for control of hybrid systems face with two main important challenging problems which are guaranteeing the stability and the computational complexity. In this article a new approach has been proposed to guarantee the closed loop stability of a class of hybrid systems while reducing the complexity of control problem by introducing some level of suboptimality. It has been shown that using contraction constraint on the objective function results in asymptotically stable closed loop system. It has also been described that since only feasibility is sufficient for stability in the proposed approach, suboptimal control could be used to reduce the computational complexity. | 2006 |
| Using Adaptive Control in Picture Stabilizer | Abdorreza Rahmati, Ali Khaki Sedigh, Asghar Taheri | This paper describes the implementation of picture stabilizer in 3-degree of freedom table in image stabilizer. There are two innovative aspects of this work. First, parameter estimation is used to adapt the feedforward compensation terms instead of the gains of the feedback controller, as usually is the case in conventional indirect self-tuning regulators. Second, the complete adaptive controller has been implemented with C program and PCL812 card and encoder card and motor driver for command the motors. In result one method with hybrid increase accuracy system, specially when input error signal is large and need to maximum speed control system. In this system frequency of 0.3 Hz , thus we use gyro for estimate of table position. In this paper, it is specifically implemented and demonstrated on a gyro mirror line-of sight (LOS) system | 2006 |
| A novel design approach for multivariable quantitative feedback design with tracking error specifications | Seyyed Mohammad Mahdi Alavi, Ali Khaki-Sedigh, Batool Labibi | In this paper, a novel Two-Degree-Of-Freedom (2DOF) design procedure for Multi-Input Multi-Output Quantitative Feedback Theory (MIMO QFT) problems with Tracking Error Specifications (TESs) is presented. In the proposed procedure, the feedback compensator design is separated from the pre-filter design, using the model matching approach and the unstructured uncertainty modeling concept. This paper specially deals with an appropriate transformation of the MIMO system to the equivalent SISO problems, which allows easy design. Simulation results have been provided to show the effectiveness of the proposed methodology. | 2006 |
| An Optimization-based Framework for Route Selection in Communication Networks | Jalal Habibi, Behzad Moshiri, Ali Khaki Sedigh | This paper introduces a new approach for routing in telecommunication networks. In this approach some theoretical foundations from mathematical modeling theory and integer programming have been exploited to develop a framework for routing problems. Some binary variables are assigned to the network links and for each link the corresponding binary variable shows the presence of the corresponding link on a specified route. The optimal route is determined in the source router per connection request by optimization of an objective function. An estimate of the residual bandwidth of network links is maintained in the source router. This information is used in the optimization problem to select the best available route from the source router to the destination router based on the selected metric. Required characteristics of a route are specified as logical constraints on the optimization variables. By using some tools … | 2006 |
| NON-AFFECTIVE ACUTE REMITTING PSYCHOSIS IN IRAN ROOZBEH HOSPITAL, 2002-2004 | J ALAGHBANDRAD, M BROUMAND, HOMAYOUN AMINI, V SHARIFI, A OMID, ASHTIANI R DAVARI, A SEDIGH, F MOUMENI, POOR Z AMINI | Background: The aim of this study was to investigate the concept of’Nonaffective Acute Remitting Psychosis'(NARP) in a group of first episode psychotic patients admitted to a psychiatric hospital in Tehran, Iran. Materials and Methods: The data are from a 24-month follow-up study of 54 first-episode non-organic psychotic patients admitted consecutively to an acute care academic hospital in | 2006 |
| Reconfigurable control system design using eigenstructure assignment: static, dynamic and robust approaches | A Esna Ashari*, A Khaki Sedigh, MJ Yazdanpanah | New approaches to design static and dynamical reconfigurable control systems are proposed based on the eigenstructure assignment techniques. The methods can recover the nominal closed-loop performance after a fault occurrence in the system, in the state and output feedback designs. These methods are capable of dealing with order-reduction problems that may occur in an after-fault system. The problem of robust reconfigurable controller design, which makes the after-fault closed-loop system insensitive as much as possible, to the parameter uncertainties of the after-fault model is considered. Steady state response of the after-fault system under the unit step input is recovered by the means of a reconfigurable feed-forward compensator. The methods guarantee the stability of the reconfigured closed-loop system in the case of output feedback. For the faulty situations, in which the order of the pre-fault and … | 2005 |
| A novel data fusion approach in an integrated GPS/INS system using adaptive fuzzy particle filter | Ali Asadian, Behzad Moshiri, Ali Khaki Sedigh | In this paper we propose a new data fusion method based on particle filtering and fuzzy logic in order to adaptively integrate global positioning system and strapdown inertial navigation system (GPS/SDINS). This approach will reduce the dependence of the stable solution on stochastic properties of the system which is a function of vehicle dynamics and environmental conditions So the proposed scheme will enhance the estimation performance in comparison with generic particle filter specially in the case of facing modeling uncertainty. It will also give us more reliable solution when encountering satellite signal blockage as a probable problem in land navigation. The results have clearly demonstrated that the hybrid fuzzy particle filter would improve the guidance from the point of accuracy and robustness to the mentioned problems. | 2005 |
| Adaptive control of chaos in nonlinear discrete-time systems using time-delayed state feedback | A Yazdanpanah, A Khaki-Sedigh | A new approach to adaptive control of chaos in non-linear discrete time systems with delayed state feedback is presented. In the case of unknown or time varying chaotic plants, the Lyapunov exponents may vary during the plant operation. In this paper, Lyapunov exponents are used to select the controller gain. An effective adaptive strategy for on-line identification of Lyapunov exponents is proposed. Simulation results are provided to show the effectiveness of the proposed methodology. | 2005 |
| Adaptive control of chaos in nonlinear chaotic discrete-time systems | Am Yazdanpanah, A Khaki-Sedigh, Ar Yazdanpanah | A model-based approach to adaptive control of chaos in non-linear chaotic discrete time systems is presented. In the case of unknown or time varying chaotic plants, the Lyapunov exponents may vary during the plant operation. In this paper, an effective adaptive strategy is proposed for on-line identification of Lyapunov exponents. The control aim is that the plant output changes in accordance with the output of the linear desired model. Simulation results are provided to show the effectiveness of the proposed methodology. | 2005 |
| Pre-filter design for tracking error specifications in MIMO-QFT | SM Mahdi Alavi, Ali Khaki Sedigh, Batool Labibi | This paper presents a novel approach to solve the MIMO-QFT problem for tracking error specification through a method of obtaining exact bounds for the design of individual elements of pre-filter. The paper specifically deals with the appropriate transformation of the MIMO system to the equivalent SISO problems, which allows easy design to find the feedback compensator and pre-filter. A linearized model of quadruple-tank process is used to show the effectiveness of the proposed method. | 2005 |
| Hybrid modeling and optimal control of a two-tank system as a switched system | H Mahboubi, B Moshiri, SA Khaki | In the past decade, because of wide applications of hybrid systems, many researchers have considered modeling and control of these systems. Since switching systems constitute an important class of hybrid systems, in this paper a method for optimal control of linear switching systems is described. The method is also applied on the two-tank system which is a much appropriate system to analyze different modeling and control techniques of hybrid systems. Simulation results show that, in this method, the goals of control and also problem constraints can be satisfied by an appropriate selection of cost function. | 2005 |
| Reconfigurable sliding-mode control design using genetic algorithms and eigenstructure assignment | A Esna Ashari, Mohammad Javad Yazdanpanah, A Khaki Sedigh | This paper proposes a reconfigurable control system design methodology using the sliding-mode control. The advantage of the proposed sliding-mode reconfigurable control methodology is that it is more robust than the simple static reconfigurable feedback. An approach is suggested to redesign the sliding surface for the after-fault variable structure controller using the genetic algorithms. So, the new sliding-mode controller is capable of preserving much of the dynamics of the original unfailed system. Simulation results are provided to show the effectiveness of the proposed method. | 2005 |
| Hybrid modeling and predictive control of a multi-tank system: A mixed logical dynamical approach | Jalal Habibi, Behzad Moshiri, Ali Khaki Sedigh | Mixed logical dynamical (MLD) modeling appears as an effective and realistic approach in modeling and control of hybrid systems. In this modeling approach, dynamical and logical constraints as well as control system design specifications are transformed into so-called mixed-integer inequalities. In this paper, the MLD framework is used for modeling of a multi-tank system as a switched nonlinear system. Control of fluid levels in multiple tanks is considered as a case study for predictive control of MLD systems. Translation of control problem specifications into mixed-integer inequalities shows the ability of MLD framework to deal with complex modeling and optimization tasks | 2005 |
| Optimal design of robust adaptive controllers a QFT-EEAS based approach using random optimization techniques | A Khaki Sedigh, O Namaki-Shoushtari, BN Araabi | Quantitative design of robust control systems proposes a transparent and practical controller design methodology for uncertain plants. In the case of large plant uncertainties, the resulted robust controller would be unnecessarily high order with large bandwidth. On the other hand, adaptive controllers can also tackle the control of unknown uncertain plants. However, the controller would be nonlinear and time varying. In this paper, a combined design methodology based on quantitative feedback theory (QFT) and externally excited adaptive system (EEAS) is proposed. This controller can handle large plant parameter uncertainties with lower bandwidth. Also, a random optimization technique is employed to optimally design the overall robust adaptive controller. Simulation results are used to show the effectiveness of the proposed design methodology. | 2005 |
| Output feedback reconfigurable controller design using eigenstructure assignment: post fault order change | A Esna Ashari, A Khaki Sedigh, MJ Yazdanpanah | This paper proposes a reconfigurable controller design method for multivariable systems, which is capable of dealing with order-change problems that may occur in an after-fault system. A new method is proposed to recover the nominal closed-loop performance after a fault occurrence in the system. This approach uses the eigenstructure assignment. Unlike the previously developed approaches, the new method can be implemented in the case when the fault leads to order change of the after-fault model. Also, it can be used to solve the problems in which the set of after-fault open-loop and closed-loop eigenvalues have common elements, especially when the system becomes uncontrollable or unobservable due to the fault. The method guarantees the stability of the reconfigured closed-loop system in the presence of output feedback. Finally, simulation results are provided to show the effectiveness of the proposed … | 2005 |
| Stock Price Modeling and Forecasting Using Stochastic Differential Equations | H Khalouzadeh, SEDIGH A KHAKI | Time series processes can be classified to three models, linear models, stochastic models and chaotic models. Based on these classification the linear models are forecastable, the stochastic models are unforecastable and the chaotic models are semi forecastaable. The previouse researches in the modeling and forecasting of the stock price usually try to prove that, the fluctuations of the share prices in Tehran Stock Exchange are not random walks in spite of the existance similarity to the random walks. Indeed the market has a chaotic behavior. This means that, the Efficient Market Hypothesis (EMH) is failed. Therefore by using a complex and powerfull models such as artificial neural networks, one can forecast stock prices in tehran stock merket. This paper proposed another approach to modeling and forecasting of the share price. This approach is based on the Stochastic Differential Equations. The modeling is based on the Black-Scholes pricing model. Comparison the simulation result with the linear ARIMA model, indicates that the proposed structrure, provides an accurate next step and the long term share prices and daily returns forecasting. | 2005 |
| Inverse Optimal Controller Design Using CLFs Obtained from Feedback Linearization | A Shahmansoorian, B Moshiri, A Khaki Sedigh, S Mohammadi | In this paper, the performance of inverse optimal controllers with respect to CLF’s which obtained from feedback linearization has been investigated. It has been shown that the use of these CLF’s in Sontag’s formula generally generates a conservative suboptimal solution for an optimization problem [1],[4]. In addition, the gain margins of inverse optimal control laws based on these CLF’s is studied. | 2005 |
| Ga based data fusion approach in an intelligent integrated gps/ins system. | Ali Asadian, Behzad Moshiri, Ali Khaki-Sedigh, Caro Lucas | A new concept regarding to the GPS/INS integration, based on artificial intelligence here is presented. Most integrated inertial navigation systems (INS) and global positioning systems (GPS) have been implemented using the Kalman filtering technique with its drawbacks related to the need for predefined INS error model and observability of at least four satellites. Most recently, an INS/GPS integration method using a hybridadaptive network based fuzzy inference system (ANFIS) has been proposed in literature. During the availability of GPS signal, the ANFIS is trained to map the error between the GPS and the INS. Then it will be used to predict the error of the INS position components during GPS signal blockage. As ANFIS will be employed in real time applications, the change in the system parameters (eg, the number of membership functions, the step size, and step increase and decrease rates) to achieve the minimum training error during each time period is automated. This paper introduces a genetic optimization algorithm that is used to update the ANFIS parameters with the INS/GPS error function used as the objective function to be minimized. The results demonstrate the advantages of the genetically optimized ANFIS for INS/GPS Integration in comparison with conventional ANFIS specially in the cases when facing satellites’ outages. Coping with this problem plays an important role in assessment of the fusion approach in land navigation. | 2005 |
| COMBINING CONTEXT AND EMOTIONAL TEMPORAL DIFFERENCES LEARNING IN CONTROLS ENGINEERING | J Abdi, F Rashidi, C Lucus, A Khaki Sedigh | COMBINING CONTEXT AND EMOTIONAL TEMPORAL DIFFERENCES LEARNING IN CONTROLS ENGINEERING Toggle navigation Home Browse Current Issue By Issue By Author By Subject Author Index Keyword Index Journal Info About Journal Aims and Scope Editorial Board Publication Ethics Indexing and Abstracting Related Links FAQ Peer Review Process Journal Metrics News Guide for Authors Submit Manuscript Reviewers Contact Us Login Login Register Persian COMBINING CONTEXT AND EMOTIONAL TEMPORAL DIFFERENCES LEARNING IN CONTROLS ENGINEERING Document Type : Article Authors J. Abdi 1 F. Rashidi 1 C. Lucus 1 A. Khaki Sedigh 2 1 Technical School, Department of Electrical and Computer Engineering, Tehran University 2 Technical School, Department of Electrical and Computer Engineering, Khaje – Nasir -Toosi University of Technology Abstract – Keywords – Sharif … | 2005 |
| Design of first order stable controller to achieve defined characteristics | Alireza Doodman Tipi, Ali Khaki Seddigh, Hassan Mohammadi Abdar | 2005 | |
| Model based method for estimating an attractor dimension from uni/multivariate chaotic time series with application to Bremen climatic dynamics | M Ataei, B Lohmann, A Khaki-Sedigh, C Lucas | In this paper, a method for estimating an attractor embedding dimension based on polynomial models and its application in investigating the dimension of Bremen climatic dynamics are presented. The attractor embedding dimension provides the primary knowledge for analyzing the invariant characteristics of the attractor and determines the number of necessary variables to model the dynamics. Therefore, the optimality of this dimension has an important role in computational efforts, analysis of the Lyapunov exponents, and efficiency of modeling and prediction. The smoothness property of the reconstructed map implies that, there is no self-intersection in the reconstructed attractor. The method of this paper relies on testing this property by locally fitting a general polynomial autoregressive model to the given data and evaluating the normalized one step ahead prediction error. The corresponding algorithms are … | 2004 |
| Adaptive calculation of Lyapunov exponents from time series observations of chaotic time varying dynamical systems | A Khaki-Sedigh, M Ataei, B Lohmann, C Lucas | This paper considers the adaptive computation of Lyapunov Exponents (LEs) from time series observations based on the Jacobian approach. It is shown that the LEs can be calculated adaptively in the face of parameter variations of the dynamical system. This is achieved by formulating the regression vector properly and adaptively updating the parameter vector using the Recursive Least-Squares principles. In cases where the structure of the dynamical system is unknown, a general non-linear regression vector for local model fitting based on a locally adaptive algorithm is presented. In this case, the Recursive Least-Squares method is used to fit a suitable local model, then by state space realization in canonical form, the Jacobian matrices are computed which are used in the QR factorization method to calculate the LEs. This method essentially relies on recursive model estimation based on output data. Hence, this on-line dynamical modeling of the process will circumvent the computations typically required in the reconstructed state space. Therefore, difficulties such as the problem of large number of data and high computational effort and time are avoided. Finally, simulation results are presented for some well-known and practical chaotic systems with time varying parameters to show the effectiveness of the proposed adaptive methodology. | 2004 |
| Risk factor of failure to thrive in less than 2 years old children Namin | M Berak, L AzariNamin, A Nemati, N Abbasgholizadeh, M Mirzarahimi, A Sedigh | 2004 | |
| Control of multivariable systems based on emotional temporal difference learning controller | C Lucas, Mehrdad Fatourechi, GholamHassan Famil Khalili, Javad Abdi, Ali Khaki-Sedigh | One of the most important issues that we face in controlling delayed systems and non-minimum phase systems is to fulfill objective orientations simultaneously and in the best way possible. In this paper proposing a new method, an objective orientation is presented for controlling multi-objective systems. The principles of this method is based an emotional temporal difference learning, and has a neuro-fuzzy structure. The proposal method, regarding the present conditions, the system action in the part and the controlling aims, can control the system in a way that these objectives are attain in the least amount of time and the best way. To clarify the issue and verify the proposed the method, three well known control examples which are hard to handle through classic methods are handled by means of the proposed method. | 2004 |
| Design of bearing-only vision-based tracking filters | Mohammad Hossein Ferdowsi, Parviz Jabehdar Maralani, Ali Khaki Sedigh | We investigate tracking filters in electro-optical target-tracking systems with bearing-only measurements and a stationary tracker. In passive tracking, for maintaining the target in the camera field of view, two tracking angles should be controlled. To extract the target position, there is at least one frame period latency resulting from time duration required for image processing. Three filtering methods, a simple Kalman filter, a novel filtering approach based on curve fitting on time series data, and an interactive multiple model filter, are studied. Since target range is neither available nor observable, in the all mentioned techniques, instead of applying filters to the target states (position and velocity in the space), each filter is directly applied to the tracking angles. The performance of each filter in this approach is evaluated by tracking angles error with two maneuvering targets. © 2004 Society of Photo-Optical Instrumentation … | 2004 |
| Optimal design of the variable structure IMM tracking filters using genetic algorithms | A Vahabian, A Khaki Sedigh, A Akhbardeh | Genetic algorithms for optimization of the multiple model and variable structure estimators are discussed in this paper. The estimation algorithm based on the multiple model and variable structure, are the best approach used in many systems, including maneuvering target tracking, noise recognition, etc. The RAMS algorithm, asserts that a multiple model algorithm consists of three steps: model set adaptation, initialization of model-based filters, and estimation. The first step, i.e., model set adaptation, is unique for VSMM algorithm and is the only superiority of the VSMM over FSMM. After the graph theory is used for this step and the sub-optimal switching digraph algorithm is discussed, we try to use the genetic algorithm for optimizing the thresholds used in the sub-optimal algorithm. The simulations show the improvement of the system performance when we use the optimal variable structure multiple model approach. | 2004 |
| Reconfigurable controller design using eigenstructure assignment and genetic algorithms | A Esna Ashari, A Khaki Sedigh | This paper proposes a reconfigurable controller design method in the case that full state feedback is not permissible. A new sufficient condition to guarantee the stability of output feedback reconfigurable controller is suggested. Based on the new condition, an algorithm is introduced that preserves much of the dynamics of the original unfailed system using eigenstructure assignment and genetic algorithms. The new algorithm guarantees the closed-loop stability of the reconfigured system. | 2004 |
| A QFT approach to robust control of automobiles active suspension | Ali M Amani, Ali K Sedigh, MJ Yazdanpanah | One of the most important problems which affect the performance of active suspension system is variation in suspension parameters such as tire stiffness, mass of body, etc. In this paper two robust approaches are applied to active suspension: H/sub /spl infin// and QFT. The performance of these two controllers is examined in the presence of parameter variation and actuator nonlinear dynamics. Simulation results show that QFT is effective in the robust control of active suspensions in automobiles and so it is useful for automobile engineers to think about using this algorithm in automobiles. | 2004 |
| Failure to thrive risk factors among infants in Namin | براک, آذری نمین, نعمتی, عباسقلی زاده, ناطق, میرزا رحیمی, صدیق, انوشیروان | Background & Objective Failure To Thrive (FTT) refers to the insufficient physical growth or inability in keeping the desired growth rate in a period to time. It is a problem in Iran as far as hygienic nutrition is concerned. FTT is a multifactor problem which is caused by various organic and nonorganic agents. This study was conducted to pinpoint the major risk factors involved in the growth of children under 2 years of age who are the most vulnerable age-group in terms of growth disorders. Methods This case-control study was conducted in 2002-2003 on 120 infants (60 cases with FTT and 60 controls) in Namin health centers. The case group was under the third percentage of their growth chart or they had -2SD in growth chart at least in three months. The control group was composed of infants with normal growth chart. The demographic characteristics of parents, and the nutritional and antropometric (height/weight, head circumference) characteristics of the subjects were measured. The collected data were analyzed by SPSS software, using chi-square and ANOVA. Results The findings indicated higher frequency of respiratory infections, diarrhea and vomiting in case group (p<0.05). The control group, on the other hand, outnumbered the case group in terms of the number of infants under 6 months who were exclusively breast-fed (p<0.05). Most of the infants with FTT had a lower birth weight than control group (p<0.05). The number of mothers with lower level of education and those who were housewives and also the number of family members were significantly higher in case group than control group (p< 0.05). However, no significant difference … | 2004 |
| On the approximation of pseudo linear systems by linear time varying systems | M Samavat, SEDIGH A KHAKI, SP Banks | This paper presents a modified method for approximating systems by a sequence of linear time varying systems. The convergence proof is outlined and the potential of this methodology is discussed. Simulation results are used to show the effectiveness of the proposed method. | 2004 |
| Multivariable Systems Temporal Difference Emotional Control | J Abdi, C Lucas, AK Sedigh, M Fatourechi | In this paper an objective orientation is presented for controlling multi-objective systems. The principles of this method is based on an emotional learning and temporal difference learning, and has a neuro-fuzzy structure. The proposal method can control the system in a way that objectives such as the present conditions, the system action in the part and the controlling aims are attained in the best way and least amount of time. | 2004 |
| FORECASTING METHODS EVALUATION OF STOCK PRICES AND PROPOSING A NONLINEAR MODEL USING NEURAL NETWORKS | H KHALOUZADEH, SEDIGH A KHAKI | In this paper, we deal with several time series of share prices and daily returns of different companies which are members of the Tehran Stock Exchange. Three prediction methods are used for time series forecasting. The first method, is based on the linear models (ARIMA) for short term and long term forecasting. The second method, is based on the nonlinear neural nenvorks model and the third method is a neural networks model with a special structure. It has been shown the time series generator process of these companies are complex nonlinear mappings and the methods based on the various linear modelling strategies are unable to identify these dynamics. Also, it has been shown by using the conventional structure of the nonlinear neural networks that one can not obtain a satisfactory results for long term forecasting. Finally, it is shown that the proposed structrure, provides accurate next step and the long term share prices and daily returns forecasting. | 2004 |
| Decentralized stabilization of large-scale systems via state-feedback and using descriptor systems | Batool Labibi, Boris Lohmann, Ali Khaki Sedigh, Parviz Jabedar Maralani | In this paper a new method for decentralized stabilization of a large-scale system in general form via state-feedback is presented. An appropriate descriptor system is defined for a large-scale system, such that the new system is in input-decentralized form. The interactions between the subsystems are considered as uncertainty. Sufficient conditions for stability of the closed-loop uncertain system are introduced. By appropriately assigning the eigenstructure of each isolated subsystem, these conditions are satisfied. This is accomplished by using the method suggested by Patton and Liu, such that the effects of the interconnections between the subsystems are compensated via the combination of genetic algorithms and gradient-based optimization. | 2003 |
| Identification of the dynamics of the google’s ranking algorithm | A Khaki Sedigh, Mehdi Roudaki | Among the search engines, Google is one of the most powerful. It uses an accurate ranking algorithm to order web pages in search results. In this paper, it is shown that a simple linear model can approximately model the dynamics governing the behaviour of Google. Least Squares is used for the system identification procedure. Identification results are provided to show the effectiveness of the identified system. | 2003 |
| Robust decentralized stabilization of large-scale systems via eigenstructure assignment | Batool Labibi, Boris Lohmann, Ali Khaki Sedigh, P Jabedar Maralani | In this paper, the problem of achieving robust stability for linear large-scale systems by decentralized feedback is considered. Sufficient conditions for stability of closed-loop system are introduced. By appropriately assigning the eigenstructure of each isolated subsystem via output feedback or state feedback, these conditions are satisfied. Based on the eigenstructure assignment result and the matrix eigenvalue sensitivity theory, a method for decentralized robust stabilization is presented. | 2003 |
| Emotional learning as a new tool for development of agent-based systems | Mehrdad Fatourechi, Caro Lucas, AK Sedig | 2003 | |
| Estimating the Lyapunov exponents of chaotic time series: A model based method | Mohammad Ataei, Ali Khaki-Sedigh, Boris Lohmann, Caro Lucas | In this paper, the problem of Lyapunov Exponents (LEs) computation from chaotic time series based on Jacobian approach by using polynomial modelling is considered. The embedding dimension which is an important reconstruction parameter, is interpreted as the most suitable order of model. Based on a global polynomial model fitting to the given data, a novel criterion for selecting the suitable embedding dimension is presented. By considering this dimension as the model order, by evaluating the prediction error of different models, the best nonlinearity degree of polynomial model is estimated. This selected structure is used in each point of the reconstructed state space to model the system dynamics locally and calculate the Jacobian matrices which are used in QR factorization method in the LEs estimation. This procedure is also applied to multivariate time series to include information from other time series … | 2003 |
| Determination of embedding dimension using multiple time series based on singular value decomposition | M Ataei, A Khaki-Sedigh, B Lohmann, C Lucas | Extracting the dynamical structure of chaotic nonlinear systems from a sequence of measurements requires a suitable state space reconstruction. This reconstruction can be expressed as the problem of embedding the time series data in a state space. The dimension of this space, embedding dimension, has a key role in the modeling of the process. Based on embedding theorems, univariate time series are generically sufficient to make state space reconstruction. However, in practice there is no guarantee that the given univariate time series is sufficient to reconstruct the dynamical structure of the process. In this paper, singular value decomposition approach for computing the optimum embedding dimension is considered. The inefficiency of the method for some univariate time series is shown. To resolve this problem, the idea of using interaction between multiple time series is presented. Extension of the method for multivariate time series is accomplished. Finally, simulation results are provided to present the above mentioned ideas in benchmark chaotic dynamical systems. | 2003 |
| Determining embedding dimension from output time series of dynamical systems-Scalar and multiple output cases | M Ataei, A Khaki-Sedigh, B Lohmann, C Lucas | 2003 | |
| Robust decentralized control of large-scale systems via H ∞ theory and using descriptor system representation | Batool Labibi, Boris Lohmann, A Khaki Sedigh, P Jabedar Maralani | In this paper, a method for design of linear decentralized robust controllers for a class of uncertain large-scale systems in general form is presented. For a given large-scale system, an equivalent descriptor system in input–output decentralized form is defined. Using this representation, closed-loop diagonal dominance sufficient conditions are derived. It is shown that by appropriately minimizing the weighted sensitivity function of each isolated subsystem, these conditions are achieved. Solving the appropriately defined H∞ local problem for each isolated uncertain subsystem, the interactions between the subsystems are reduced, and the overall stability and robust performance are achieved in spite of uncertainties. The designs are illustrated by a practical example. | 2003 |
| Relative gain array analysis of uncertain multivariable plants | Ali Khaki-Sedigh, Bijan Moaveni | The input-output pairing of multivariable plants with parametric uncertainty can vary in the face of large plant parameter variations. The Relative Gain Array (RGA) analysis is a powerful tool for the input-output pairing of linear multivariable plants. In the case of parametric uncertainties, RGA elements may vary accordingly. Hence, a test is proposed to identify the change in the input-output pairing in the presence of parametric uncertainties. | 2003 |
| Model Based Method for Determining the Minimum Embedding Dimension from Chaotic Time Series-Univariate and Multivariate Cases | M Ataei, B Lohmann, A Khaki-Sedigh, C Lucas | The problem of embedding dimension estimation from chaotic time series based on polynomial models is considered. The optimality of embedding dimension has an important role in computational efforts, Lyapunov exponents analysis, and efficiency of prediction. The method of this paper is based on the fact that the reconstructed dynamics of an attractor should be a smooth map, ie with no self intersection in the reconstructed attractor. To check this property, a local general polynomial autoregressive model is fitted to the given data and a canonical state space realization is considered. Then, the normalized one step ahead prediction error for different orders and various degrees of nonlinearity in polynomials is evaluated. This procedure is also extended to a multivariate form to include information from other time series and resolve the shortcomings of the univariate case. Besides the estimation of the embedding … | 2003 |
| A novel method for decentralized robust exponential stabilization of large-scale systems | Batool Labibi, Yazdan Bavafa-Toosi, Ali Khaki-Sedigh, Boris Lohmann | A novel approach to the design of decentralized controllers for large-scale systems by dynamic/static output state feedback is presented. A new formulation of the interaction which introduces some degrees of freedom into the design procedure is offered. Sufficient conditions for exponential stability with desirable rate of decay and maximal robustness to unstructured uncertainties in the controller and plant parameters are established. The derived conditions are generic, applicable to nonsquare and nonminimum-phase systems, and independent of the number of system states, inputs and outputs. Based on minimal sensitivity design of isolated subsystems, an analytical method for the satisfaction of the aforementioned sufficient conditions is presented. To this end, through eigenstructure assignment, compact-form sufficient conditions for minimal sensitivity are derived. Illustrative examples are presented to … | 2003 |
| Optimal Design of Robust Quantitative Feedback Controllers Using Linear Programming and Genetic Algorithms | Vaheed S Bokharaie, Ali Khaki-Sedigh | Quantitative Feedback Theory (QFT) is one of most effective methods of robust controller design and can be considered as a suitable method for systems with parametric uncertainties. Particularly it allows us to obtain controllers less conservative than other methods like and -synthesis. In QFT method, we transform all the uncertainties and desired specifications to some boundaries in Nichols chart and then we have to find the nominal loop transfer function such that satisfies the boundaries and has the minimum high frequency gain. The major drawback of the QFT method is that there is no effective and useful method for finding this nominal loop transfer function. The usual approach to this problem involves loop-shaping in the Nichols chart by manipulating the poles and zeros of the nominal loop transfer function. This process now aided by recently developed computer aided design tools proceeds by trial and error and its success often depends heavily on the experience of the loop-shaper. Thus for the novice and First time QFT user, there is a genuine need for an automatic loop-shaping tool to generate a first-cut solution. In this paper, we approach the automatic QFT loop-shaping problem by using an algorithm involving Linear Programming (LP) techniques and Genetic Algorithm (GA). | 2003 |
| Estimating the lyapunov exponents of chaotic time series based on polynomial modelling | M Ataei, A Khaki-Sedigh, B Lohmann | The problem of Lyapunov Exponents (LEs) estimation from chaotic data based on Jacobian approach by polynomial models is considered. The optimum embedding dimension of reconstructed attractor is interpreted as suitable order of model. Therefore, based on global polynomial mode ling of system, a novel criterion for selecting the embedding dimension is presented. By considering this dimension as the model order, the best nonlinearity degree of polynomial is estimated. The selected structure is used for local estimating of Jacobians to calculate the LEs. This suitable structure of polynomial model leads to better results and avoids of sporious LEs. Simulation results show the effectiveness of proposed methodology. | 2003 |
| Solving weighted mixed sensitivity H∞ problem by decentralized control feedback via modifying weighting functions and using descriptor system representation | Batool Labibi, Ali Khaki Sedigh, Parviz Jabedar Maralani, Boris Lohmann | This paper considers the problem of achieving stability and certain performance for a large-scale system by a decentralised control feedback law. For a given large-scale system an equivalent descriptor system in input-output decentralised form is defined. For solving the performance problem which is formulated as the standard weighted mixed sensitivity H∞ problem, modification of the original weighting functions is proposed. Some sufficient conditions are proposed when satisfied the overall stability and performance of the large-scale system is guaranteed. | 2003 |
| Evaluating methods of the share price forecastability in Tehran stock exchange | H KHALOUZADEH, SEDIGH A KHAKI | In this paper, we deal with several time series of daily share prices and daily returns of different companies which are members of the Tehran Stock Exchange. Three forecastability methods as nonlinear mathematical analysis were applied to the data obtained for daily share prices and daily returns in Tehran Stock Exchange during three and half years. The characteristics of the process associated with these time series were analyzed. | 2003 |
| ADAPTIVE INPUT-OUTPUT PAIRING USING ON-LINE RGA IDENTIFICATION | A Khaki Sedigh, B Moaveni | Control structure design in the face of large plant parameter variations is an important step in the design of reconfigurable decentralized multivariable controllers. In this paper, recursive least square estimators (RLS) are used for on-line relative gain array (RGA) identification. Therefore, input-output pairing can be updated in the face of large plant parameter variations. Copyright© 2003 IFAC | 2003 |
| Truncated Temporal Difference with Function Approximators: Some successful examples by CMAC | Javad Abdi, Caro Lucas, Ali Khaki Sedigh, Azam Famil Khalili | 2003 | |
| An LMI Approach to Automatic Loop-Shaping of QFT Controllers | Vaheed S Bokharaie, Ali Khaki-Sedigh | Quantitative Feedback Theory (QFT) is one of effective methods of robust controller design. In QFT design we can considers the phase information of the perturbed plant so it is less conservative than and -synthesis methods and as be shown, it is more transparent than the sensitivity reduction methods mentioned. In this paper we want to overcome the major drawback of QFT method which is lack of an automatic method for loop-shaping step of the method so we focus on the following problem: Given a nominal plant and QFT bounds, synthesize a controller that achieves closed-loop stability and satisfies the QFT boundaries. The usual approach to this problem involves loop-shaping in the frequency domain by manipulating the poles and zeros of the nominal loop transfer function. This process now aided by recently developed computer aided design tools proceeds by trial and error and its success often depends heavily on the experience of the loop-shaper. Thus for the novice and First time QFT user, there is a genuine need for an automatic loop-shaping tool to generate a first-cut solution. Clearly such an automatic process must involve some sort of optimization, and while recent results on convex optimization have found fruitful applications in other areas of control theory we have tried to use LMI theory for automating the loop-shaping step of QFT design. | 2003 |
| A Combined Method for Automatic QFT Loop-Shaping Using Linear Programming and Genetic Algorithm | VS Bokharaie, A Khaki-Sedigh | A Combined Method for Automatic QFT Loop-Shaping Using Linear Programming and Genetic Algorithm :: MPG.PuRe English Help Privacy Policy Disclaimer Include files Advanced SearchBrowse START BASKET (0)Tools Item ITEM ACTIONSEXPORT Add to Basket Local TagsRelease HistoryDetailsSummary Released Meeting Abstract A Combined Method for Automatic QFT Loop-Shaping Using Linear Programming and Genetic Algorithm MPS-Authors There are no MPG-Authors in the publication available External Resource http://folk.ntnu.no/skoge/prost/proceedings/afcon03/Papers/PreliminaryProgramme.pdf (Table of contents) Fulltext (restricted access) There are currently no full texts shared for your IP range. Fulltext (public) There are no public fulltexts stored in PuRe Supplementary Material (public) There is no public supplementary material available Citation Bokharaie, V., & Khaki-Sedigh, A. (2003). A … | 2003 |
| Optimal Design of Robust Quantitative Feedback Controllers Using Linear Programming and Genetic Algorithms | Ali Khaki-Sedigh, Vaheed S Bokharaie | Quantitative Feedback Theory (QFT) is one of most effective methods of robust controller design and can be considered as a suitable method for systems with parametric uncertainties. Particularly it allows us to obtain controllers less conservative than other methods like H∞ and µ-synthesis. In QFT method, we transform all the uncertainties and desired specifications to some boundaries in Nichols chart and then we have to find the nominal loop transfer function such that satisfies the boundaries and has the minimum high frequency gain. The major drawback of the QFT method is that there is no effective and useful method for finding this nominal loop transfer function. The usual approach to this problem involves loop-shaping in the Nichols chart by manipulating the poles and zeros of the nominal loop transfer function. This process now aided by recently developed computer aided design tools proceeds by trial and … | 2003 |
| Solving weighted mixed sensitivity H∞problem by decentralised control feedback | A Khaki-Sedigh, P Jabedar Maralani, B Lohmann | This paper considers the problem of achieving stability and certain H ∞ performances for a large-scale system by a decentralised control feedback law. The performance problem is formulated as a standard weighted mixed sensitivity H ∞ problem. Then, to solve the proposed problem a modification of the original weighting functions is presented. Some sufficient conditions are introduced to ensure the overall stability and performance of the large-scale system. Finally, an example is used to show the effectiveness of the proposed methodology. | 2003 |
| A novel approach to linear decentralized robust performance stabilization of large-scale systems | Batool Labibi, Yazdan Bavafa-Toosi, Ali Khaki-Sedigh, Boris Lohmann | The existing methods of decentralized control suffer from two major restrictions. First, almost all of them hinge on Lyapunov’s method, and second, they do not address the problem of performance robustness. A novel methodology to overcome the above defects is presented in this paper. Central to this approach is the notion of a finite-spectrum-equivalent descriptor system in the input-output decentralized form. By way of this notion, a new formulation of the interaction which introduces some degrees of freedom into the design procedure is offered. The main result, i.e. a sufficient condition for decentralized performance stabilization in a desirable performance region and maximal robustness to unstructured uncertainties in the controller and plant parameters, nevertheless, is in terms of regular systems. Based on minimal sensitivity design of isolated subsystems via eigenstructure assignment, an analytic method for … | 2003 |
| Performance improvement of active suspension system using mixed H/sub 2//H/sub/spl infin//technique | AM Amani, MJ Yazdanpanah, AK Sedigh | In this paper, a mixed H/sub 2//H/sub /spl infin// controller is designed for 1/4 car suspension model. Neither H/sub 2/ nor H/sub /spl infin// controllers can provide goals of active suspension separately (i.e. minimizing body vertical acceleration considering restriction on suspension displacement). So, in this paper both objectives are considered in a mixed H/sub 2//H/sub /spl infin// problem. The Riccati equations are solved using a recursive algorithm and the mixed H/sub 2//H/sub /spl infin// controller performance is compared with H/sub 2/ and H/sub /spl infin// controllers through frequency and time domain simulations. | 2003 |
| Robust Tracking by Using Measure Theory | A Zare, A Khaki-Sedigh, A Vahidian | This paper presents two new approaches for robust step tracking in structure uncertain nonlinear systems. The problem is first restated as a non linear optimal control infinite horizon problem, then with a suitable change of variable, the time interval is transfer to the finite horizon [0 1). This change of variable, poses a time varying problem. This problem is then transfer to measure space, and it is shown that an optimal measure must be determined which is equivalent to a linear programming problem with infinite dimension. Then, using finite horizon approximations, the optimal control law is determined as a piece wise constant function. Simulations are provided to show the effectiveness of the proposed methodology | 2003 |
| Online Manuscript Access | Batool Labibi, Yazdan Bavafa-Toosi, Ali Khaki-Sedigh, Boris Lohmann | A novel approach to the design of decentralized controllers for large-scale systems by dynamicstatic output state feedback is presented. A new formulation of the interaction which introduces some degrees of freedom into the design procedure is offered. Sufficient conditions for exponential stability with desirable rate of decay and maximal robustness to unstructured uncertainties in the controller and plant parameters are established. The derived conditions are generic, applicable to nonsquare and nonminimum-phase systems, and independent of the number of system states, inputs and outputs. Based on minimal sensitivity design of isolated subsystems, an analytical method for the satisfaction of the aforementioned sufficient conditions is presented. To this end, through eigenstructure assignment, compact-form sufficient conditions for minimal sensitivity are derived. Illustrative examples are presented to … | 2003 |
| THE USING OF MEASURE THEORY IN MINIMAL TIME OF OPTIMAL CONTROL PROBLEMS | A ZAREA, SEDIGH A KHAKI, AV KAMYAD | This paper presents a new approach for solving of time optimal control in nonlinear problem using measure theory. This problem is transfer to measure space, and it is shown that an optimal measure must be determined which is equivalent to a linear programming problem with infinite dimension. Afterward, by suitable approximation it changes to a finite-dimensional linear programming. By solving the LP problems, optimal control function can determine such as a piecewise constant function. | 2003 |
| Output feedback decentralized control of large-scale systems using weighted sensitivity functions minimization | Batool Labibi, Boris Lohmann, A Khaki Sedigh, P Jabedar Maralani | This paper considers the problem of achieving stability and desired dynamical transient behavior for linear large-scale systems, by decentralized control. It can be done by making the effects of the interconnections between the subsystems arbitrarily small. Sufficient conditions for stability and diagonal dominance of the closed-loop system are introduced. These conditions are in terms of decentralized subsystems and directly make a constructive H∞ control design possible. A mixed H∞ pole region placement is suggested, such that by assigning the closed-loop eigenvalues of the isolated subsystems appropriately, the eigenvalues of the overall closed-loop system are assigned in desirable range. The designs are illustrated by an example. | 2002 |
| Minimum sensitivity in linear output feedback design | YAZDAN Bavafa-Toosi, A Khaki-Sedigh | Necessary and sufficient conditions for minimum sensitivity (highest robustness) to unstructured uncertainty in linear output feedback design are presented. The approach is analytical and simple, and the solution is explicit, in compact form, and restriction-free. Genetic algorithm is employed to implement the proposed method. | 2002 |
| DECENTRALISED QUANTITATIVE FEEDBACK DESIGN OF LARGE-SCALE SYSTEMS | B Labibi, B Lohmann, A Khaki Sedigh, P Jabedar Maralani | In this paper a new method for robust decentralised control of large-scale systems using quantitative feedback theory (QFT) is suggested. For a given large-scale system an equivalent descriptor system is defined. Using this representation, closed-loop diagonal dominance sufficient conditions over the uncertainty space are derived. It is shown by appropriately choosing output disturbance rejection model in designing QFT controller for each isolated subsystem, these conditions are achieved. Then a single-loop quantitative feedback design scheme is applied to solve the resulting series of individual loops to guarantee the satisfaction of predefined MIMO quantitative specifications. | 2002 |
| Reducing control effort by means of emotional learning | M Fatourechi, C Lucas, A Khaki Sedigh | 2001 | |
| Reduction of maximum overshoot by means of emotional learning | M Fatourechi, C Lucas, A Khaki Sedigh | 2001 | |
| An Agent-based Approach to Multivariable Control | M Fatourechi, C Lucas, A Khaki Sedigh | 2001 | |
| Design of static linear multivariable output feedback controllers using random optimization techniques | Ali Khaki-Sedigh, Yazdan Bavafa-Toosi | New necessary and sufficient conditions for multivariable pole placement (MVPP) and entire eigenstructure assignment (EEA) through static linear multivariable output feedback are established. It is shown that the resultant matrix is of full rank and all design freedoms are retained. The problem of static linear multivariable output feedback control law design is then defined. Based on the EEA concept and sufficiency of the regional pole placement, the design is (re) formulated in terms of a constrained nonlinear optimization problem. To this end, some decoupling indices for noninteractive performance are defined, their necessary and sufficient conditions are derived and tracker design is addressed. The problem formulation well suits the application of random/intelligent optimization techniques. By way of this approach, optimal robust stability/performance, noninteractive performance, reliability, actuator limitations and … | 2001 |
| Long term prediction of Tehran price index (TEPIX) using neural networks | Hamid Khaloozadeh, A Khaki Sedigh | It has been previously shown that the dynamics governing the share prices in Tehran Stock Exchange can be considered as a chaotic time series. Due to the initial sensitivity of the price generating process, it is shown that linear classical models such as ARIMA and ARCH are not able to efficiently model the dynamic of share prices in Tehran stock exchange for long term prediction purposes. However, non-linear neural network models are proposed to model the Tehran price index (TEPIX) daily data process and it is shown that such nonlinear models can successfully be used for the long term prediction of TEPIX daily data. Real data for the period of 1996 to 1999 are used to validate the prediction results. | 2001 |
| Leveling and gyrocompassing of stable platforms using neural networks | SEDIGH A KHAKI, SARVI M NASIRI | This paper presents the application of neural networks for the adaptive leveling and gyrocompassing of stable platforms. The stable platform is a three input and two output nonlinear plant, and the control of its error dynamics (leveling) is of vital importance for the proper operation of the inertial navigation systems of aircraft. Also, another important preflight step in the inertial navigation system using the stable platform is gyrocompassing. Gyrocompassing provides the navigation system with the wander angle, which is the angle between the Y-axis of the stable platform and true north. | 2001 |
| Design of decentralized high-gain error-actuated controllers for large-scale systems | B Labibi, B Lohmann, A Khaki Sedigh, P Jabedar Maralani | In this article a high-gain decentralized controller is designed for a large-scale system. The effects of the interactions between the subsystems are considered as uncertainty for the large-scale system. A bound on the high-gain factor is computed to nullify the effects of the interactions and also to ensure the overall closed-loop stability. In order to avoid saturation, the anti-windup integrator method is used in designing high-gain controller. Due to high-gain feedback, the closed-loop system is robust with respect to output disturbances and uncertainties. | 2001 |
| Optimal dynamic routing controllers | A Azhari-Khameneh, A Khaki-Sedigh, K Mohamedpour | In this paper three centralized controllers for circuit-switched networks are presented. These include a dynamic routing strategy based on the state-information of network in binary form, optimal dynamic routing strategy based on probability method and optimal dynamic routing strategy based on gradient method. The last two methods are based on the network circuit group status and traffic status. The networks considered can be symmetric, or non-symmetric, hierarchical or non-hierarchical (fully connected, or two-link route, … multi-link route). In these controllers, the number of link-path is limited, and the number of nodes can be exceeded more than hundred. The first dynamic routing Controller can be used as an Event-Dependent Routing and the two last controllers can be used as a State-Dependent Routing or Optimal Dynamic Routing, according to the state of the network. The selection of routes is based on multiple constraints such as, minimum number of nodes, least loaded route, least loaded progressive selection path, least loaded recursive selection path, preplanned route, elimination of unauthorized altemative route according to the request. The simulation results are provided to show the effectiveness of the proposed methods. | 2001 |
| Optimal design of robust quantitative feedback controllers using random optimization techniques | A Khaki Sedigh, Caro Lucas | Quantitative design of robust control systems proposes a transparent and practical controller design methodology for uncertain single-input single-output and multivariable plants. There are several steps involved in the design of such controllers. The main steps involved in the design are template generation, loop shaping and pre-filter design. In the case of multivariable uncertain plants, manipulation of tolerance bounds within the available freedom, for both sequential and non-sequential designs, consideration of template size of next step in sequential design, and the appropriate selection of the nominal transfer function matrices in the equivalent disturbance attenuation design are also crucial steps. In all the quantitative designs, a time-consuming trial-and-error procedure is adapted and a successful compromise between various design requirements is very much dependent on the designer experience and … | 2000 |
| Sufficient condition for stability of decentralised control | B Labibi, B Lohmann, A Khaki Sedigh, P Jabedar Maralani | A new sufficient condition is presented for the overall stability of decentralised linear control systems. This condition is in terms of the eigenvalues of the Hermitian part of the interaction matrix and the Hermitian part of the state matrix of each closed-loop isolated subsystem. | 2000 |
| Decentralized robust control of large-scale systems via sensitivity reduction to the interactions | B Labibi, B Lohmann, A Khaki Sedigh, PJ Maralani | The problem of achieving stability and certain H/sub /spl infin// performance objective for a large-scale system by a decentralized feedback law is considered. It is shown in order to reduce the sensitivity to the interactions, the states of the other subsystems can be considered as external disturbances for each subsystem. An appropriate H/sub /spl infin// controller is designed for each subsystem. Solving H/sub /spl infin// problems for the subsystems, the sensitivity to the interactions is reduced and the performance problem which is formulated as the standard weighted mixed sensitivity H/sub /spl infin// problem, is solved. Sufficient conditions are derived when satisfied to assure the overall stability. | 2000 |
| Genetic Methodology for Linear Output Feedback Control Law Design | Y Bavafa-Toosi, A Khaki-Sedigh | The multivariable linear output feedback technique is recast as a constrained nonlinear optimization problem. An evolutionary, multiple-objective genetic algorithm is applied to encapsulate and globally optimally reconcile stability, robustness, performance enhancement, reliability, actuator limitations, numerical and computational pitfalls, and tracking and regulation, faced to structured or unstructured system uncertainties. The potentials and e ectiveness of the proposed method are substantiated by simulation results. | 2000 |
| On the Predictability of Price Fluctuations in Tehran Stock Exchange A Correlation Dimension Estimation Approach | H Khaloozadeh, A Khaki Sedigh, C Lucas | This paper employs a general non-linear analysis tool to analyse the nature of time series associated with the price (returns) of a particular company in Tehran Stock Exchange. It is shown that the behavior of the process associated with the price (returns) time-series of this company is weakly chaotic, and due to the non-random behavior of the process, short term prediction of stock price is possible. It is also shown, using the correlation dimension estimation analysis, that a modeling of the price fluctuations based solely on the price data is insufficient to establish a model for future price prediction and that other variables involved in the process must be accounted for. | 1999 |
| Controller design using, μ-synthesis for static VAR compensator to enhance the voltage profile for remote induction motor loads | M Abedi, SA Taher, AK Sedigh, H Seifi | This paper deals with the design and implementation of a robust controller for the static VAR compensator (SVC) in remote industrial power system, to enhance the voltage profile for three phase single cage induction motor (SCIM) loads. The controller design is based on μ-synthesis method to deal with uncertainties arising in industrial network modeling. The performance of the controller has been evaluated extensively by non-linear time domain simulation. It is concluded that the robust controller enhances the voltage profile for SCIM loads compared with conventional SVC type (CSVC), which consist of voltage and current feedback loops. | 1998 |
| H&infin Controller Design for Static VAR Compensators in Industrial Networks | M Abedi, SA Taher, AK Sedigh, H Seifi | This paper deals with the design and evaluation of a robust controller for static VAR compensator (SVC) in remote industrial power systems to enhance the voltage profile for three-phase single cage induction motor (SCIM) loads. The controller design is based on H∞ theory to deal with uncertainties arising in industrial network modelling. The performance of the H∞ controller has been evaluated extensively through non-linear time domain simulation. It is concluded that the robust controller (RSVC) enhances the voltage profile for SCIM loads compared with the optimal (OSVC) type which consists of optimal state feedback (LQR). | 1998 |
| Design and Implementation of a Predictive Fuzzy Controller for an Industrial Furnace | AK Sedigh, N Afshar, M Afazeli | A predictive fuzzy controller is designed and implemented for an industrial furnace. The furnace temperature is controlled so as to track the reference profiles accurately, and to reject the disturbances. A RLS on-line predictor is used to predict future values of the plant’s output. Using these predicted values, the future error values with respect to the reference profiles are evaluated. With regard to these errors, the fuzzy controller inferences the input power to be delivered to the furnace in order to eliminate the future tracking error. | 1997 |
| Input-output pairing using balanced realisations | A Khaki-Sedigh, A Shahmansourian | Using the balanced realisations of a multivariable plant, input-output pairing can be achieved, which is the most suitable pairing for the design of decentralised, sequential closing type multivariable controllers. In the approach proposed by the authors, states are used as the interface variables between the inputs and the outputs of the plant. | 1996 |
| Design of robust power system stabilizers (PSS) using quantitative feedback theory | AK Sedigh, G Alizadeh | The adaptive stabilizer can overcome the problem of parameter variations but will result in a very complex control system compared to the conventional or even state-feedback type stabilizers. It also has its own problems such as convergence or stability in the presence of unmodelled dynamics. To overcome the problem of parameter variations and to maintain the simplicity of the stabilizer for practical implementations, a robust power system stabiliser (PSS) is proposed in this paper using the quantitative feedback theory. In the present design the power system under consideration is a single synchronous generator connected to an infinite bus through a transmission line. The control ratio is modelled, the templates of the power system are formed for a wide range of frequencies, the U-Contour and different bounds for power system uncertainties are determined. After shaping the open-loop transfer function of the … | 1994 |
| On Line Identification of the First Markov Parameter of Linear Multivariable Plants (RESEARCH NOTE) | J Kamali, Ali Khaki-Sedigh | In this paper three methods for on-line identification of first markov parameter at linear multivariable plants are presented. In these methods input-output data are used far the on-line identification of the first markov parameter. | 1994 |
| Design of tunable digital set-point tracking controllers for linear multivariable type-one plants | B Porter, A Khaki-Sedigh | Since many industrial processes are essentially linear multivariable type-one plants (i.e. linear multivariable plants with unbounded step-response matrices but with bounded impulse-response matrices), the methodologies of Porter and Jones (1986) for linear multivariable type-zero plants are extended to embrace such linear multivariable type-one plants. It is shown that the proportional and derivative controller matrices in the resulting PD controllers can be directly determined from open-loop impulse-response tests performed on linear multivariable type-one plants. The disturbance-rejection properties of these controllers are fully developed by modifying the digital PD controller by the inclusion of an outer PID loop. The robustness propertcs of these PD-PID controllers are assessed by characterizing, in terms of the steady-state impulse-response matrices of nominal and actual plants, the admissible plant … | 1990 |
| Design of tunable and adaptive digital set-point tracking controllers for linear multivariable plants. | A Khaki-Sedigh | The methodology for the design of tunable and adaptive digital set-point tracking controllers for linear multivariable plants with bounded step-responses matrices (ie type-zero systems), proposed by Porter and co-workers, has been shown to provide a practical solution to the problem of designing digital control systems for unknown, dynamically complex multivariable type-zero plants. In this thesis, the design of such tunable and adaptive digital controllers is generalised to include plants with completely unbounded step-response matrices (ie type-one plants) and also plants with partially bounded step-response matrices (ie mixed type-one/type-zero plants). The robustness and disturbance-rejection properties of these tunable digital set-point tracking controllers for linear multivariable type-zero, type-one, and mixed type-one/type-zero plants are studied. In addition, the robustness properties of the adaptive digital set … | 1990 |
| Design of Adaptive Digital Set-Point Tracking Controllers Incorporating Recursive Impulse-Response Matrix Identifiers for Type-One Multivariable Plants | B Porter, A Khaki-Sedigh | It is shown that, by incorporating on-line recursive identifiers to provide updated steady-state impulse-response matrices for inclusion in digital proportional-plus-derivative control laws, highly effective adaptive digital set-point tracking controllers can be readily designed for marginally stable type-one multivariable plants. The effectiveness of such an adaptive controller is illustrated by designing an adaptive digital set-point tracking controller for a ‘difficult’ type-one multivariable plant. | 1990 |
| Robustness properties of tunable digital set-point tracking PID controllers for linear multivariable plants | B Porter, A Khaki-Sedigh | The robustness properties of tunable digital set-point tracking PID controllers are assessed. This assessment is effected by characterizing, in terms of the steady-state transfer function matrices of nominal and actual plants, the admissible plant perturbations that can be tolerated by such tunable digital PID controllers. The resulting robustness theorem is illustrated by designing an autopilot for a missile in the form of a tunable digital set-point tracking PID controller. | 1989 |
| Design of digital set-point tracking PID controllers for hydrofoils | B Porter, A Khaki-Sedigh | Marine vehicles, and hydrofoils in particular, are complex multivariable plants with significant levels of open-loop interaction. It is difficult to obtain explicit mathematical models for such vehicles, and the effort involved is frequently wasted because marine vehicles usually exhibit significant plant-parameter variations. There is therefore a requirement for a methodology for the design of digital controllers for marine vehicles which is simply applicable to highly interactive multivariable plants, does not require explicit mathematical models, and is equally applicable to both fixed-parameter and variable-parameter plants. In order to circumvent the need for mathematical models in either state space or transfer function matrix form, and to avoid performance degradation, Jones and Porter (1987) introduced adaptive digital PID controllers. Such adaptive controllers incorporate online recursive identifiers which provide updated … | 1988 |
| Design of robust adaptive digital setpoint tracking Pl controllers incorporating recursive step-response matrix identifiers for gas turbines | B Porter, A Khaki-Sedigh | It is shown that, by incorporating fast on-line recursive identifiers to provide updated step-response matrices for inclusion in digital proportional-plus-integral control laws, highly robust adaptive digital setpoint tracking PI controllers can be readily designed for multivariable plants. The effectiveness of this methodology is illustrated by designing an adaptive digital setpoint tracking PI controller for a gas turbine using both exactly parametrised and grossly under-parametrised models. | 1988 |
| Design of digital set-point tracking PID controllers for warships | B Porter, A Khaki-Sedigh | In order to circumvent the need for mathematical models of multivariable plants expressed in either state-space or transfer function matrix form, tunable digital PID controllers were introduced by Porter and Jones (1986). The controller matrices can be directly determined from open-loop tests performed on asymptotically stable plants. However, although such controllers are intrinsically robust, some degradation in closed-loop behaviour inevitably occurs in the case of large plant parameter variations. In order to avoid such performance degradation, adaptive digital PID controllers were therefore introduced by Jones and Porter (1987). Such controllers incorporate fast online recursive identifiers which provide updated step-response matrices for inclusion in control laws with the structure of the earlier controllers. The effectiveness of these controllers is illustrated by examples of tunable and adaptive digital set-point … | 1988 |
| Design of Robust Adaptive Digital Set-Point Tracking P1 Controllers for Nonminimum-Phase Multivariable Plants | B Porter, A Khaki-Sedigh | It is shown that, by incorporating on-line recursive identifiers to provide updated steady-state plant transfer function matrices for inclusion in digital proportional-plus-integral control laws, highly robust adaptive digital set-point tracking PI controllers can be readily designed for nonminiraum-phase multivariable plants. The effectiveness of this methodology in the absence of precise a priori information concerning plant order is illustrated by designing an adaptive digital set-point tracking PI controller for a distillation column with nonminimum-phase characteristics using both exactly parametrised and grossly underparametrised models. | 1988 |
| Singular perturbation analysis of the step-response matrices of a class of linear multivariable systems | B Porter, A Khaki-Sedigh | Singular perturbation methods are used to demonstrate that the step-response matrices of linear multivariable systems containing small ‘parasitic” elements have a distinctive structure which guarantees the robustness of both non-adaptive and adaptive controllers for such systems incorporating step-response matrices. The significance of these results in relation to the modelling of multivariable plants with ‘fast” actuators and sensors is illustrated, and their validity is demonstrated by considering a typical gas-turbine jet engine. | 1987 |
| Heave Disturbance Attenuation for the Offshore Managed Pressure Drilling Systems Under the Input Time-Delay and Time-Varying Parameter Uncertainties Using an Equivalent-Input … | Mobina Abolghasemi, Amirhossein Nikoofard, Ali Khaki-Sedigh | Managed pressure drilling (MPD) is a process to control the drilling of non-drillable oil and gas wells or wells with narrow pressure ranges. In an offshore MPD system, the heave disturbance caused by the sea waves makes severe bottom hole pressure (BHP) fluctuations. Additionally, the input time-delay and time-varying parameter uncertainties can cause serious accidents in the system. In this paper, a delay-dependent guaranteed-cost control based on the equivalent-input-disturbance (EID) approach is designed to control the BHP and maintain the system stability in the concurrent presence of the heave disturbance, the input time-delay, and uncertainties. Comparison results with two common industrial controllers, sliding mode control (SMC) and proportional-integral-derivative (PID) are demonstrated to show the effectiveness of the EID approach using the root mean square error (RMSE) index as a comparison metric. Then, the system sensitivity and robustness to the time-delay parameter and measurement noise presence are respectively investigated. | |
| Distributed Economic Data-Driven Koopman Predictive Control for Solar Parabolic-Trough Collector Field | Ali Khaki-Sedigh, Tahereh Gholaminejad | In this paper, a data-driven distributed economic Koopman predictive control strategy to control the parabolic-trough solar collector loops is presented to maximize the thermal energy collected by these fields. The solar plant is subject to a coupled constraint on the control inputs and time-varying disturbances such as solar radiation and ambient temperature. Although the collector loops are dynamically decoupled, cooperation between them is required due to the coupling constraint between loops and the time-varying disturbances acting on each loop. By constructing cooperative clusters including collector loops with different received disturbance magnitudes, where the cluster members can change in different time scales according to the time-varying disturbance, both the economic cost function optimization and the coupling constraint satisfaction can be attained. The local predictive controller optimization problems in each cluster are based on a data-driven Koopman predictive control scheme which is solved sequentially in each cluster and parallel to the other clusters. Finally, the proposed controller is compared to the centralized and decentralized data-driven in the tracking-based and economic-based MPC methods. The results show that the energy efficiency of the proposed scheme outperforms that of traditional and compared controllers, and the method is implementable in real-time to control large-scale solar collector fields of more than 1000 loops. | |
| Research Article Analysis of a Chaotic Memristor Based Oscillator | F Setoudeh, A Khaki Sedigh, M Dousti | A chaotic oscillator based on the memristor is analyzed from a chaos theory viewpoint. Sensitivity to initial conditions is studied by considering a nonlinear model of the system, and also a new chaos analysis methodology based on the energy distribution is presented using the Discrete Wavelet Transform (DWT). Then, using Advance Design System (ADS) software, implementation of chaotic oscillator based on the memristor is considered. Simulation results are provided to show the main points of the paper. | |
| Implementation of an Improved Performance Integral | Mahdy Rezaei Darestani, AmirAli Nikkhah, Ali KhakiSedigh | Abstract to enhance the closed loop performance in presence of disturbance, uncertainties and delay a double loop mixture of MPC and robust controller is proposed. This double loop controller ensures smooth tracking for a 3-axis gyro-stabilized platform which has delay intrinsically. This control idea is suggested to eliminate high frequency disturbances and minimize steady state error with minimum power consumption in simulation and experiment. Proposed controller based on the combination of ℋ2 and ℋ∞ controllers in the inner control loop shows the robustness of the proposed methodology. In the outer loop to have a good tracking performance, an integrated MPC is used to handle delay in system dynamics. Also, the main idea for dealing with uncertainties is using integral and derivative of platform attitude. In the proposed platform, the ℋ∞ controller is compared with ℋ∞/ℋ2 controller in KNTU laboratory in theory and experiment. Results of experimental set up shows the same reaction of two controllers against disturbance and uncertainties in delayed system. | |
| RESEARCH NOTE ON THE APPROXIMATION OF PSEUDO LINEAR SYSTEMS BY LINEAR TIME VARYING SYSTEMS | M Samavat, A Khaki Sedigh, SP Banks | This paper presents a modified method for approximating nonlinear systems by a sequence of linear time varying systems. The convergence proof is outlined and the potential of this methodology is discussed. Simulation results are used to show the effectiveness of the proposed method. | |
| of Mathematics, zyxwvutsrqponmlkjihg | ALI KHAKI-SEDIGH | Necessary and sufficient condit, ions for minimum seiisitivit, y (highest robustness) to unstructured uncertainty in linear output feedback design are presented. The approach is analytical and simple, and the solution is explicit, in compact form, and restriction-free. Genetic algorithm is employed to implement the proposed met, hod. | |
| ECC 2003—Session Index 8 | T Schweickhardt, F Allgower, FJ Doyle III, R Holland, P Young, C Zhu, I Szaszi, P Iordanov, MJ Hayes, M Halton, IA Griffin, PJ Fleming, B Labibi, Y Bavafa-Toosi, A Khaki-Sedigh, B Lohmann, JS Welsh, GC Goodwin | In this paper the problem of vehicle lateral control in highway experimental conditions is addressed. The vehicle under consideration is equipped with an electric motor acting on the steering angle (the command input) and a vision system providing two measurements (the two outputs): the lateral displacement and the angular orientation of the vehicle with respect to the lane centerline. We show how, exploiting properties of single-input two-outputs systems, our original SITO control problem can be simplified to the design of a SISO controller. The design of such a controller is performed through-synthesis techniques in order to obtain robust performance in the face of model uncertainties. Experimental results obtained testing the designed controller on highways are reported. | |
| On the Predictability of Tehran Price Index (TEPIX) | Hamid Khaloozadeh, Ali Khaki Sedigh | Using nonlinear mathematical analysis, on the data obtained for Tehran Price Index (TEPIX) during 3.5 years, the characteristics of the process associated with TEPIX is analyzed. Analyzing the behavior of the time series associated with TEPIX is indicative of its short-term predictability nature. However, employing analysis regarding the correlation dimension estimate, it is indicated that, only the time series of TEPIX data are not adequate for TEPIX prediction and other appropriate variables must also be used. Also, using a Rescaledrange analysis, it is shown that past information have long term effect on the market and are useful in process prediction. Also, Largest Lyapunov Exponent analysis reveals a weakly chaotic behavior and indicates that TEPIX data cannot be used in the prediction process after a certain time. | |
| Engineers, Part I: Journal of Systems and | M Zareh, M Rezaei, J Roshanian, A Khaki-Sedigh | This paper investigates the use of an L1 adaptive controller direct approach to solve the attitude control problem of a launch vehicle (LV) during its atmospheric phase of flight. One of the most important difficulties in designing a controller for launch vehicles (LVs) is the widely changing system parameters during launch. Aerospace systems such as aircraft or missiles are subject to environmental and dynamical uncertainties. These uncertainties can alter the performance and stability of these systems. Unknown variations in thrust and atmospheric properties, eccentricities of nozzles, and other unknown conditions cause changes in a system. The L1 adaptive controller ensures uniformly bound transient and asymptotic tracking for the system’s signals–input and output–simultaneously. This adaptive control technique quickly compensates for large changes in the LV dynamics. The effect of feedback gain selection and robustness of this approach against system uncertainties and actuator disturbances are also discussed. The adaptive control method is then simulated with representative LV longitudinal motion. The effectiveness of the proposed control schemes is demonstrated through hardware-in-the-loop simulation. | |
| DELAYED FEEDBACK CONTROL OF DELAYED CHAOTIC SYSTEMS | Nastaran Vasegh, Ali Khaki Sedigh | Although there are a number of theoretical methodologies to use time delayed feedback controller for controlling chaos, useful algorithms are still lacking. In this paper, some algorithms to adjust parameters of time delayed feedback controller derived from theoretical results in time domain and frequency domain are presented. Comparison of theses approaches based on computer simulations is included. | |
| Robust Stability and performance with H2/H∞/µ controller for Single Person Aircraft | J Mashayekhi Fard, MA Nekoui, A Khaki Sedigh, R Amjadifard | In a physical system several targets are normally being considered in which each of nominal and robust performance has their own strengths and weaknesses. Nominal performance means considering system operation without uncertainty, has decisive effect on the operation of system. Robust performance means considering operation with uncertainty. This target causes intensive limitation on the controller grade and even it’s solutionless. The target of this paper is to present a new approach for balancing between nominal and robust performance, using their own gains. This will be done, using one new approach. First, the controller of H2/H∞ will be designed for nominal performance target, robust stability and noise reduction and then µ controller is designed for robust performance. By combing these two controllers and achieve their weights. Finally, Simulation and comparison studies are used to show the effectiveness and benefits of method. | |
| Aplication of a Fuzzy Controller for a Launch Vehicle in a Hardware-in-the-Loop | Mahdy Rezaei Darestani, Mehran Zare, Jafar Roshanian, Ali Khaki Sedigh | ||
| A NEW APPROACH TO INPUT-OUTPUT PAIRING ANALYSIS FOR UNCERTAIN MULTIVARIABLE PLANTS | B Moaveni, A Khaki Sedigh | In this paper, a new method to analyze the input-output pairing for uncertain multivariable plants is proposed. Here, Hankel Interaction Index Array is used to choose the appropriate input-output pair and a theorem will be presented to show the effect of additive uncertainties on input-output pairing of the system. In this theorem a new approach to compute the variation bound of Hankel Interaction Index Array elements due to additive uncertainties in state space framework is given to study the possible change in input-output pairing. Finally, two typical plants are employed to show the main points of the proposed methodology. | |
| Using predictive Control Algorithms to Wind Disturbance Rejection in XY pedestal | A Ghahramani, T Karbasi, M Nasirian, A Khaki Sedigh | In this paper, designing of a predictive controller for the elimination of the wind disturbance over the XY pedestal is investigated. XY pedestal is a two-degree-of-freedom ground station antenna which is related to the HDF pedestals (High Dynamic Full Motion Leo Satellite Tracking Pedestals). This system model is achieved by using the Dymola software. According to the comparisons, this model is very close to the actual system model with high accuracy. Purpose: is to trace a LEO orbit satellite, that of passing satellites and angles related to the antenna have been extracted path from KNTUSAT software. For simulating the wind disturbance model the Davenport filter was used. In simulations, the operation of PI controller has been optimized and Model Predictive Controller (MPC) and Generalized Predictive Controller (GPC) has been studied. The results of comparison between simulation methods shows that predictive controller has had less error in satellite tracking and has been shown less controlling effort and also has had good behavior in eliminate wind disturbance. | |
| A Combined QFT/EEAS Design Technique for Uncertain Multivariable Plants | Omid Namaki Shoushtari, Ali Khaki Sedigh, Babak Nadjar Araabi | This paper presents a robust-adaptive control design for uncertain multivariable plants based on Quantitative Feedback Theory (QFT) and Externally Excited Adaptive Systems (EEAS). Design requirements are derived and formulated in terms of different cost functions. Also, a stochastic optimization technique is employed to optimally design the overall robust adaptive controller. This controller can handle large plant parameter uncertainties with lower control gains. Simulation results are provided to show the effectiveness and features of the proposed QFT/EEAS MIMO design methodology compared with the direct MIMO QFT design approach. | |
| SHORT-TERM PREDICTION OF AIR POLLUTION USING MULTI-LAYER PERCPTERON & GAMMA NEURAL NETWORKS | M Aliyari Shoorehdeli, M Teshnehlab, A Khaki Sedigh | ‡ Dept. of Elect. Eng. KN Toosi University of Tech. Tehran, Iran. Fax:+ 98 21 846-2066 Sedigh@ eetd. kntu. ac. ir | |
| Control Lyapunov Functions and Continuous Inverse Optimal Control Laws | A Shahmansoorian, A Khaki Sedigh, B Moshiri, S Mohammadi | In this paper, has shown any Control Lyapunov function (CLF) is not necessarily the value function of a meaningful cost functional such as (8) and using a theorem of authors, a continuous optimal controller associated to these CLFs is obtained, which has proper gain margin. In addition it has shown that with a 0)(≥ xr sometimes a continuous optimal controller can be achieved. Main results of the paper are presented during the examples. | |
| Multi-Critics Based Intelligent Control | MEHRDAD FATOURECHI, CARO LUCAS, ALI KHAKI SEDIGH | A new approach for the multi-objective control of dynamic plants is presented based on the agent concept. The control system consists of a neurofuzzy controller whose weights are adapted according to emotional signals provided by blocks called emotional critics. Each critic is assigned to assess the situation of its corresponding control objective. Simulation results are provided for the control of different dynamical systems in order to clarify the matter further. | |
| CA 2008 Organizing and Program Committee | Tai-hoon Kim, Byeong-Ho KANG, Alberto Isidori, Alessandro Casavola, Ali Khaki Sedigh, Amir Hussain, Arthur J Krener, Barry Lennox, Bernard Grabot, Organisation de la Direction des Etudes, France Campi Marco, Choonsuk Oh, Christian Schmid, Chun-Yi Su, Denis Gillet, Frank Allgower, Guoping Liu, Hojjat Adeli, Hong Wang, Igor Skrjanc, Janan Zaytoon CReSTIC, France URCA, Jurek Sasiadek, Jus Kocijan, Kwanho You, Kwon S Lee, Manuel Haro Casado, Ming-yih Lee, Nina Thornhill, Pierre Borne, Rolf Johansson, Satoshi Tadokoro | Provides a listing of current committee members. | |
| stem Identification | FJ Doyle III, R Holland, P Young, C Zhu, P Gaspar, Hungarain Academ, P Iordanov, MJ Hayes, M Halton, IA Griffin, PJ Fleming, B Labibi, Y Bavafa-Toosi, A Khaki-Sedigh, B Lohmann | In this paper the problem of vehicle lateral control in highway experimental conditions is addressed. The vehicle under consideration is equipped with an electric motor acting on the steering angle (the command input) and a vision system providing two measurements (the two outputs): the lateral displacement and the angular orientation of the vehicle with respect to the lane centerline. We show how, exploiting properties of single-input two-outputs systems, our original SITO control problem can be simplified to the design of a SISO controller. The design of such a controller is performed through μ-synthesis techniques in order to obtain robust performance in the face of model uncertainties. Experimental results obtained testing the designed controller on highways are reported. | |
| Authoritative Seismic Excited Structural Control via Classical PID | Yazdan Bavafa-Toosi, Ali Khaki-Sedigh, Saeed Ghasemzadeh | Most of the current research on active structural control in the last two decades has been focused on either full-state or velocity feedback strategies to achieve authoritative aseismic protection. In this paper, through a realistic model incorporating control-structure interaction (CSI), classical PID control is attested well su cient to reconcile reliability, performance requirements, feasibility, economical implementation and maintenance. The proposed controller is based on incomplete output feedback and thus provides higher reliability and viability. The authority of the method is substantiated by performance levels better than those of some sophisticated observer-based full state H1, L1 and LQG controllers. The e ectiveness of the proposed controller is evinced by simulation results. | |
| Neural Predictive Control for Wide Range of Process Systems | Ali Jazayeri, Alireza Fatehi, Houman Sadjadian, Ali Khaki-Sedigh | In this paper a Neural Predictive Controller (NPC) designed to control a broad class of process systems. Neural network identification yields nonlinear global model of the unknown system. Levenberg-Marquardt (LM) optimization method is used to find optimal control signal to minimize future errors of the objective function of predictive controller. Inequality constraints of actuators are added to the objective function through a penalty term which increases drastically as it approaches the limitations. To use the controller for wide range of process systems, an initial phase runs before the main controller to determine parameters. This phase moves the system output to operating point and applies PID controller with APRBS reference signal. The gathered data are used to estimate parameters such as pure delay, prediction horizon, control coefficient and identification order. To validate the approaches, the controller has implemented in level, pressure and flow pilot plants and compared with conventional controller which shows faster and smoother tracking results. |
