Exponentially stable guaranteed cost control for continuous and discrete-time Takagi-Sugeno fuzzy systems

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• 作者：Bo Pang^a ; ^bAuthor Vitae ; Xiaocheng Liu^a ; ^bAuthor Vitae ; Qibing Jin^cAuthor Vitae ; Weidong Zhang^a ; ^b ; ^{wdzhang@sjtu.edu.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae
• 关键词：Exponential stability ; Convergence rate ; Guaranteed cost control (GCC) ; T&ndash ; S fuzzy system ; Linear matrix inequality (LMI)
• 刊名：Neurocomputing
• 出版年：2016
• 出版时间：12 September 2016
• 年：2016
• 卷：205
• 期：Complete
• 页码：210-221
• 全文大小：1023 K

文摘

This paper investigates exponentially stable guaranteed cost control (GCC) for a class of nonlinear systems which is represented by Takagi–Sugeno (T–S) fuzzy systems. State feedback controllers of parallel distributed compensation (PDC) structure are designed by the means of GCC for continuous and discrete-time T–S fuzzy systems respectively. GCC methods in this paper adopt quadratic performance functions, which take effects of control efforts, regulation errors and convergence rates into consideration simultaneously, to provide desirable performance and fast response for closed-loop systems. Sufficient design conditions that guarantee exponential stabilities of resulting closed-loop systems with predefined convergence rates are presented. By setting different convergence rates, response speed of the closed-loop nonlinear system can be adjusted. The proposed design procedures are eventually converted into linear matrix inequalities (LMIs) problems of minimizing upper bounds of the guaranteed cost functions. Finally, a well-known nonlinear benchmark control example and a truck–trailer example demonstrate the effectiveness and feasibility of all the proposed methods.