Indirect adaptive fuzzy control of nonlinear descriptor systems

Shamloo, Naeimeh Fakhr; Kalat, Ali Akbarzadeh; Chisci, Luigi

doi:10.1016/j.ejcon.2019.06.007

Cited by 16 publications

(9 citation statements)

References 35 publications

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“…Adaptive fuzzy controller can be divided into direct adaptive fuzzy controller (DAFC) and indirect adaptive fuzzy controller (IAFC). The main advantage of DAFC is simple in structure, but there are some limitations in the design process (Shamloo et al, 2020). IAFC allows to separate model adaption from controller design, so that the convergence of model or parameter can be analyzed separately from control performance and stability.…”

Section: Indirect Adaptive Fuzzy H∞ Speed Controlmentioning

confidence: 99%

Design and indirect adaptive fuzzy H^∞ control of a novel retarder coupled with eddy current effect and MR effect

Zhu

Chen

et al. 2020

Journal of Intelligent Material Systems and Structures

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To improve the poor braking performance of the traditional eddy current retarder, a novel retarder is developed by coupling the eddy current effect and the magnetorheological effect, which has large torque at low speed and stable torque at high speed. To meet the constant speed requirement in the braking process, the indirect adaptive fuzzy H∞ control strategy is employed to control the rotor speed of the designed retarder. The results show that the proposed retarder has the characteristics of continuously adjustable large torque in full speed section, sensitive control process and constant speed intelligent control.

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Section: Indirect Adaptive Fuzzy H∞ Speed Controlmentioning

confidence: 99%

Design and indirect adaptive fuzzy H^∞ control of a novel retarder coupled with eddy current effect and MR effect

Zhu

Chen

et al. 2020

Journal of Intelligent Material Systems and Structures

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“…The following theorem gives the sufficient conditions for the existence and stability of the observer (7).…”

Section: Observer Designmentioning

confidence: 99%

“…On the other hand, descriptor systems, also known as singular, generalized, or differential-algebraic systems, describe a large class of systems for which the standard state-space representation is not applicable. They are encountered in electrical, chemical, mineral, mechanical, and large-scale systems [4][5][6][7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

A robust state estimation for a class of uncertain linear time‐invariant descriptor systems

Jalali

Kalat

2020

Asian Journal of Control

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This paper proposes a robust state observer for linear time-invariant descriptor systems in which parametric uncertainty exists in the derivative, the system, and the input matrices of the system. The proposed approach is based on a new parameterization in state variables such that in the new model, the derivative matrix is known. An observer is suggested for estimating the state of the new model. Sufficient conditions are obtained for the convergence of the observer in the form of a linear matrix inequality (LMI), which can be solved by the YALMIP toolbox. Numerical examples accompanied by comparison are presented to demonstrate the efficient performance of the proposed observer.

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“…It is known that the control problems for normal uncertain nonlinear systems can be solved to some extent by the advanced adaptive control theory. And the adaptive control theory has been extended to solve the admissibility problems for nonlinear singular systems in References 35-37. Nevertheless, for the more complex uncertain nonlinear singular systems, and more complex control problems, such as nonlinear tracking control, a better way should be developed.…”

Section: Introductionmentioning

confidence: 99%

Observer‐based adaptive neural control for a class of nonlinear singular systems

Chen

Lin

Zhang

2020

Intl J Robust & Nonlinear

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The problem of observer-based adaptive neural control via output feedback for a class of uncertain nonlinear singular systems is studied in this article. The nonlinear singular systems can be regarded as two subsystems that are coupled with each other: differential subsystem and algebraic subsystem. The differential systems can be nonstrict feedback structures. To guarantee that the singular system is regular and impulse-free, two new conditions are proposed. By the conditions, the linear controller and observer, which are used to estimate the immeasurable state variables, are obtained. Then, an output feedback scheme through adaptive neural backstepping is proposed to ensure that all states of the closed-loop system are semiglobally uniformly ultimately bounded and converge to a small neighborhood of the origin. Simulation examples illustrate the effectiveness of the presented method. K E Y W O R D S adaptive neural control, output feedback, singular system, uncertain nonlinear system 1 Int J Robust Nonlinear Control. 2020;30:4043-4058. wileyonlinelibrary.com/journal/rnc © 2020 John Wiley & Sons, Ltd. 4043 4044 CHEN et al.nonstrict feedback systems. 11 In addition, the Newton-based observer, 19 sliding-mode, 20 and Lyapunov-based observer 21 are designed for nonlinear systems. Singular systems have been extensively studied because it can better describe the physical systems, such as power systems, economics, biological systems, and other areas. 22,23 The study of singular systems is much more complicated than that of the state-space systems because not only the stability but also the regularity and impulse-free should be considered. Recently, the study of singular systems is mainly based on the linear system theory. The observer design is addressed in References 24-27. The problems of stability analysis for singular Markovian jump systems, 28 and the admissibility for singular T-S fuzzy model 29 are studied. In References 30 and 31 , the analysis and control synthesis for singular systems with time delays are discussed. All the above results are based on linear matrix inequality (LMI) techniques. The above methods are regarded as effective methods for linear singular systems. However, for nonlinear, or uncertain singular systems, the T-S fuzzy model-based methods 22,32-34 will bring much conservatism. It is known that the control problems for normal uncertain nonlinear systems can be solved to some extent by the advanced adaptive control theory. And the adaptive control theory has been extended to solve the admissibility problems for nonlinear singular systems in References 35-37. Nevertheless, for the more complex uncertain nonlinear singular systems, and more complex control problems, such as nonlinear tracking control, a better way should be developed.In this article, an observer-based neural control scheme via output feedback is proposed for a class of uncertain nonlinear singular systems for the first time. In the proposed scheme, a reduced-order observer is constructed to estimate the unmeasured state vari...

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Indirect adaptive fuzzy control of nonlinear descriptor systems

Cited by 16 publications

References 35 publications

Design and indirect adaptive fuzzy H^∞ control of a novel retarder coupled with eddy current effect and MR effect

Design and indirect adaptive fuzzy H^∞ control of a novel retarder coupled with eddy current effect and MR effect

A robust state estimation for a class of uncertain linear time‐invariant descriptor systems

Observer‐based adaptive neural control for a class of nonlinear singular systems

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Indirect adaptive fuzzy control of nonlinear descriptor systems

Cited by 16 publications

References 35 publications

Design and indirect adaptive fuzzy H∞ control of a novel retarder coupled with eddy current effect and MR effect

Design and indirect adaptive fuzzy H∞ control of a novel retarder coupled with eddy current effect and MR effect

A robust state estimation for a class of uncertain linear time‐invariant descriptor systems

Observer‐based adaptive neural control for a class of nonlinear singular systems

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Design and indirect adaptive fuzzy H^∞ control of a novel retarder coupled with eddy current effect and MR effect

Design and indirect adaptive fuzzy H^∞ control of a novel retarder coupled with eddy current effect and MR effect