In this paper, we are interested in the survey of deterministic identification by subspace approa... more In this paper, we are interested in the survey of deterministic identification by subspace approach. To the opposite of classic recursive identification method, this new technique is well adapted to multivariable linear time invariant LTI systems described by a state space model, and of consequent order. Founded on geometric and mathematical tools of linear algebra such as matrix projection, QR decomposition and Singular Value Decomposition SVD, the subspace identification method permits to estimate a state realization directly from the only knowledge of input-output data. One proposes, in this work, to describe the method stages and its application to estimate the induction motor parameters as well as in simulation and experiment. In this purpose, the motor is described by a complex formed model in dq referential. Simulation study and experiment results are presented and discussed.
2014 15th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA), 2014
In this paper, we present an application of a Takagi Sugeno (TS) Fuzzy logic backstepping control... more In this paper, we present an application of a Takagi Sugeno (TS) Fuzzy logic backstepping control for enhancing performance of the machine drive. The equations states of induction machine are described in a d-q frame related to the rotating stator field. In the first step, the state feedback linearization technique is used for decoupling speed and flux controls. In the second step, we have been developed a control scheme basis of fuzzy backstepping. The simulation results in MATLAB environment show that the proposed scheme gives a satisfactory performance.
This article investigates the practical exponential stability and design problems of conformable ... more This article investigates the practical exponential stability and design problems of conformable time-delay systems. Sufficient conditions that confirm the practical exponential stability and design of the proposed class of systems are given by utilizing an adequate Lyapunov–Krasovskii functional (L-KF). These conditions are expressed in the form of linear matrix inequalities (LMI) which could be solved by using solvers in LMI Toolbox of MATLAB. Two numerical examples are given to illustrate the applicability of the proposed results.
Advances in Materials Science and Engineering, May 27, 2022
In this paper, robust optimal control of an uncertain wind energy conversion system (WECS), descr... more In this paper, robust optimal control of an uncertain wind energy conversion system (WECS), described by a Takagi-Sugeno fuzzy model, is proposed to guarantee the maximum power trajectory tracking (MPTT). e design of the fuzzy optimal control is based on a quadratic criterion related to the maximum power tracking error. e proposed fuzzy controller allows to regulate the recti ed direct current (DC) voltage of the variable-speed wind turbine by adjusting the duty cycle of a boost converter. Linear matrix inequality (LMI) conditions, ensuring the optimal H 2 tracking error, are proposed for the controller gain design. Simulation as well as experimental tests are performed for e ciency evaluation of the established MPPT fuzzy control scheme under variable wind speed conditions.
Structural Control and Fault Detection of Wind Turbine Systems, 2018
An augmented TS fuzzy plant model has been proposed to model the nonlinear plant subject to large... more An augmented TS fuzzy plant model has been proposed to model the nonlinear plant subject to large parameter uncertainties, sensor faults and actuator faults. Based on this augmented TS fuzzy plant model, three different methods to design the fuzzy FTC have been proposed to tackle this nonlinear system. A design procedure of fuzzy fault tolerant controllers has been developed. The stability and robustness of the fuzzy FTC systems have been investigated based on the results of Chapters 11.2 and 11.3. An application example on stabilizing a WES with sensor faults, actuator faults and parameter uncertainties has been given to illustrate the design procedure and merits of the proposed fuzzy fault tolerant controller.
International Journal of Applied Mathematics and Computer Science, 2018
Two techniques for the control of a grid side converter in a wind energy conversion system. The s... more Two techniques for the control of a grid side converter in a wind energy conversion system. The system is composed of a fixed pitch angle wind turbine followed by a permanent magnet synchronous generator and power electronic converters AC-DC-AC. The main interest is in how to control the inverter in order to ensure the stability of the DC link voltage. Two control methods based on the fuzzy approach are applied and compared. First, a direct Mamdani fuzzy logic controller is presented. Then, a T-S fuzzy controller is elaborated based on a T-S fuzzy model. The Lyapunov theorem and H-infinity performance are exploited for stability analysis. Besides, the feedback controller gains are determined using linear matrix inequality tools. Simulation results are derived in order to prove the robustness of the proposed control algorithms and to compare their performances.
This paper deals with the weighted minimum-variance self-tuning regulation of stochastic time-var... more This paper deals with the weighted minimum-variance self-tuning regulation of stochastic time-varying systems, which can be described by linear input-output mathematical models. We consider the input-output ARMAX mathematical models with unknown time-varying parameters. The recursive extended least squares RELS algorithm, which can be applied to the stochastic time-varying systems, is presented. Self-tuning regulators are developed on the basis upon the weighted minimum-variance control strategy. The developed theoretical results are applied to a heat transfer process. The obtained practical results show the good performances of the developed weighted minimum-variance self-tuning regulators.
The description and the identification of a heat transfer process are studied. For this purpose, ... more The description and the identification of a heat transfer process are studied. For this purpose, a suitable experimental setup was built: a unit of treatment and computation with a data acquirement card is used for the online identification process. Three classes of block-...
International Journal of Automation and Computing, 2014
In this paper, an analysis for ill conditioning problem in subspace identification method is prov... more In this paper, an analysis for ill conditioning problem in subspace identification method is provided. The subspace identification technique presents a satisfactory robustness in the parameter estimation of process model which performs control. As a first step, the main geometric and mathematical tools used in subspace identification are briefly presented. In the second step, the problem of analyzing ill-conditioning matrices in the subspace identification method is considered. To illustrate this situation, a simulation study of an example is introduced to show the ill-conditioning in subspace identification. Algorithms numerical subspace state space system identification (N4SID) and multivariable output error state space model identification (MOESP) are considered to study, the parameters estimation while using the induction motor model, in simulation (Matlab environment). Finally, we show the inadequacy of the oblique projection and validate the effectiveness of the orthogonal projection approach which is needed in illconditioning; a real application dealing with induction motor parameters estimation has been experimented. The obtained results proved that the algorithm based on orthogonal projection MOESP, overcomes the situation of ill-conditioning in the Hankel s block, and thereby improving the estimation of parameters.
In this paper, we are interested in the survey of deterministic identification by subspace approa... more In this paper, we are interested in the survey of deterministic identification by subspace approach. To the opposite of classic recursive identification method, this new technique is well adapted to multivariable linear time invariant LTI systems described by a state space model, and of consequent order. Founded on geometric and mathematical tools of linear algebra such as matrix projection, QR decomposition and Singular Value Decomposition SVD, the subspace identification method permits to estimate a state realization directly from the only knowledge of input-output data. One proposes, in this work, to describe the method stages and its application to estimate the induction motor parameters as well as in simulation and experiment. In this purpose, the motor is described by a complex formed model in dq referential. Simulation study and experiment results are presented and discussed.
2014 15th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA), 2014
In this paper, we present an application of a Takagi Sugeno (TS) Fuzzy logic backstepping control... more In this paper, we present an application of a Takagi Sugeno (TS) Fuzzy logic backstepping control for enhancing performance of the machine drive. The equations states of induction machine are described in a d-q frame related to the rotating stator field. In the first step, the state feedback linearization technique is used for decoupling speed and flux controls. In the second step, we have been developed a control scheme basis of fuzzy backstepping. The simulation results in MATLAB environment show that the proposed scheme gives a satisfactory performance.
This article investigates the practical exponential stability and design problems of conformable ... more This article investigates the practical exponential stability and design problems of conformable time-delay systems. Sufficient conditions that confirm the practical exponential stability and design of the proposed class of systems are given by utilizing an adequate Lyapunov–Krasovskii functional (L-KF). These conditions are expressed in the form of linear matrix inequalities (LMI) which could be solved by using solvers in LMI Toolbox of MATLAB. Two numerical examples are given to illustrate the applicability of the proposed results.
Advances in Materials Science and Engineering, May 27, 2022
In this paper, robust optimal control of an uncertain wind energy conversion system (WECS), descr... more In this paper, robust optimal control of an uncertain wind energy conversion system (WECS), described by a Takagi-Sugeno fuzzy model, is proposed to guarantee the maximum power trajectory tracking (MPTT). e design of the fuzzy optimal control is based on a quadratic criterion related to the maximum power tracking error. e proposed fuzzy controller allows to regulate the recti ed direct current (DC) voltage of the variable-speed wind turbine by adjusting the duty cycle of a boost converter. Linear matrix inequality (LMI) conditions, ensuring the optimal H 2 tracking error, are proposed for the controller gain design. Simulation as well as experimental tests are performed for e ciency evaluation of the established MPPT fuzzy control scheme under variable wind speed conditions.
Structural Control and Fault Detection of Wind Turbine Systems, 2018
An augmented TS fuzzy plant model has been proposed to model the nonlinear plant subject to large... more An augmented TS fuzzy plant model has been proposed to model the nonlinear plant subject to large parameter uncertainties, sensor faults and actuator faults. Based on this augmented TS fuzzy plant model, three different methods to design the fuzzy FTC have been proposed to tackle this nonlinear system. A design procedure of fuzzy fault tolerant controllers has been developed. The stability and robustness of the fuzzy FTC systems have been investigated based on the results of Chapters 11.2 and 11.3. An application example on stabilizing a WES with sensor faults, actuator faults and parameter uncertainties has been given to illustrate the design procedure and merits of the proposed fuzzy fault tolerant controller.
International Journal of Applied Mathematics and Computer Science, 2018
Two techniques for the control of a grid side converter in a wind energy conversion system. The s... more Two techniques for the control of a grid side converter in a wind energy conversion system. The system is composed of a fixed pitch angle wind turbine followed by a permanent magnet synchronous generator and power electronic converters AC-DC-AC. The main interest is in how to control the inverter in order to ensure the stability of the DC link voltage. Two control methods based on the fuzzy approach are applied and compared. First, a direct Mamdani fuzzy logic controller is presented. Then, a T-S fuzzy controller is elaborated based on a T-S fuzzy model. The Lyapunov theorem and H-infinity performance are exploited for stability analysis. Besides, the feedback controller gains are determined using linear matrix inequality tools. Simulation results are derived in order to prove the robustness of the proposed control algorithms and to compare their performances.
This paper deals with the weighted minimum-variance self-tuning regulation of stochastic time-var... more This paper deals with the weighted minimum-variance self-tuning regulation of stochastic time-varying systems, which can be described by linear input-output mathematical models. We consider the input-output ARMAX mathematical models with unknown time-varying parameters. The recursive extended least squares RELS algorithm, which can be applied to the stochastic time-varying systems, is presented. Self-tuning regulators are developed on the basis upon the weighted minimum-variance control strategy. The developed theoretical results are applied to a heat transfer process. The obtained practical results show the good performances of the developed weighted minimum-variance self-tuning regulators.
The description and the identification of a heat transfer process are studied. For this purpose, ... more The description and the identification of a heat transfer process are studied. For this purpose, a suitable experimental setup was built: a unit of treatment and computation with a data acquirement card is used for the online identification process. Three classes of block-...
International Journal of Automation and Computing, 2014
In this paper, an analysis for ill conditioning problem in subspace identification method is prov... more In this paper, an analysis for ill conditioning problem in subspace identification method is provided. The subspace identification technique presents a satisfactory robustness in the parameter estimation of process model which performs control. As a first step, the main geometric and mathematical tools used in subspace identification are briefly presented. In the second step, the problem of analyzing ill-conditioning matrices in the subspace identification method is considered. To illustrate this situation, a simulation study of an example is introduced to show the ill-conditioning in subspace identification. Algorithms numerical subspace state space system identification (N4SID) and multivariable output error state space model identification (MOESP) are considered to study, the parameters estimation while using the induction motor model, in simulation (Matlab environment). Finally, we show the inadequacy of the oblique projection and validate the effectiveness of the orthogonal projection approach which is needed in illconditioning; a real application dealing with induction motor parameters estimation has been experimented. The obtained results proved that the algorithm based on orthogonal projection MOESP, overcomes the situation of ill-conditioning in the Hankel s block, and thereby improving the estimation of parameters.
Uploads
Papers by Maher Kharrat