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Fuzzy Adaptive Controller for Uncertain Multivariable Nonlinear Systems with Both Sector Nonlinearities and Dead-Zones

Fuzzy Adaptive Controller for Uncertain Multivariable Nonlinear Systems with Both Sector Nonlinearities and Dead-Zones

Abdesselem Boulkroune
Copyright: © 2017 |Pages: 29
ISBN13: 9781522519089|ISBN10: 1522519084|EISBN13: 9781522519096
DOI: 10.4018/978-1-5225-1908-9.ch022
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MLA

Boulkroune, Abdesselem. "Fuzzy Adaptive Controller for Uncertain Multivariable Nonlinear Systems with Both Sector Nonlinearities and Dead-Zones." Fuzzy Systems: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2017, pp. 487-515. https://doi.org/10.4018/978-1-5225-1908-9.ch022

APA

Boulkroune, A. (2017). Fuzzy Adaptive Controller for Uncertain Multivariable Nonlinear Systems with Both Sector Nonlinearities and Dead-Zones. In I. Management Association (Ed.), Fuzzy Systems: Concepts, Methodologies, Tools, and Applications (pp. 487-515). IGI Global. https://doi.org/10.4018/978-1-5225-1908-9.ch022

Chicago

Boulkroune, Abdesselem. "Fuzzy Adaptive Controller for Uncertain Multivariable Nonlinear Systems with Both Sector Nonlinearities and Dead-Zones." In Fuzzy Systems: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 487-515. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-5225-1908-9.ch022

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Abstract

This chapter presents two fuzzy adaptive variable structure controllers for a class of uncertain multi-input multi-output nonlinear systems with actuator nonlinearities (i.e. with sector nonlinearities and dead-zones). The design of the first controller concerns systems with symmetric and positive definite control-gain matrix, while the design of the second one is extended to the case of non-symmetric control-gain matrix thanks to an appropriate matrix decomposition, namely the product of a symmetric positive-definite matrix, a diagonal matrix with diagonal entries +1 or -1, and a unity upper triangular matrix. An appropriate adaptive fuzzy-logic system is used to reasonably approximate the uncertain functions. A Lyapunov approach is adopted to derive the parameter adaptation laws and prove the stability of the closed-loop control system. Finally, some simulation results are carried out to show the effectiveness of the proposed controllers.

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