Relaxed Stability and Performance LMI Conditions for Takagi-Sugeno Fuzzy Systems With Polynomial Constraints on Membership Function Shapes

被引：112

作者：

Sala, Antonio ^{[1
]}

Arino, Carlos ^{[2
]}

机构：

[1] Univ Politecn Valencia, Dept Syst Engn & Control, E-46022 Valencia, Spain

[2] Jaume I Univ, Ind Syst Engn & Design Dept, E-12080 Castellon de La Plana, Spain

来源：

IEEE TRANSACTIONS ON FUZZY SYSTEMS | 2008年 / 16卷 / 05期

关键词：

Linear matrix inequality (LMI); parallel distributed compensation (PDC); polynomial fuzzy systems; quadratic stability; relaxed condition; Takagi-Sugeno (T-S) fuzzy control;

D O I：

10.1109/TFUZZ.2008.926585

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Most linear matrix inequality (LMI) fuzzy control results in literature are valid for any membership function, i.e., independent of the actual membership shape. Hence, they are conservative (with respect to other nonlinear control approaches) when specific knowledge of the shapes is available. This paper presents relaxed LMI conditions for fuzzy control that incorporate such shape information in the form of polynomial constraints, generalizing previous works by the authors. Interesting particular cases are overlap (product) bounds and ellipsoidal regions. Numerical examples illustrate the achieved improvements, as well as the possibilities of solving some multiobjective problems. The results also apply to polynomial-in-membership Takagi-Sugeno fuzzy systems.

引用

页码：1328 / 1336

页数：9

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