Stability analysis of polynomial fuzzy models via polynomial fuzzy Lyapunov functions

被引：47

作者：

Bernal, Miguel ^{[1
]}

Sala, Antonio ^{[2
]}

Jaadari, Abdelhafidh ^{[3
]}

Guerra, Thierry-Marie ^{[3
]}

机构：

[1] Sonora Inst Technol, Dept Elect & Elect Engn, Obregon, Sonora, Mexico

[2] Univ Politecn Valencia, Inst Automat & Informat Ind AI2, Valencia, Spain

[3] Univ Valenciennes & Hainaut Cambresis, LAMIH FRE CNRS 3304, Valence, France

来源：

FUZZY SETS AND SYSTEMS | 2011年 / 185卷 / 01期

关键词：

Local stability; Fuzzy modeling; Fuzzy Lyapunov functions; Polynomial fuzzy models; Sum of squares; NONLINEAR-SYSTEMS; LMI CONDITIONS; STABILIZATION; PERFORMANCE; SUM;

D O I：

10.1016/j.fss.2011.07.008

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In this paper, the stability of continuous-time polynomial fuzzy models by means of a polynomial generalization of fuzzy Lyapunov functions is studied. Fuzzy Lyapunov functions have been fruitfully used in the literature for local analysis of Takagi-Sugeno models, a particular class of the polynomial fuzzy ones. Based on a recent Taylor-series approach which allows a polynomial fuzzy model to exactly represent a nonlinear model in a compact set of the state space, it is shown that a refinement of the polynomial Lyapunov function so as to make it share the fuzzy structure of the model proves advantageous. Conditions thus obtained are tested via available SOS software. (C) 2011 Elsevier B.V. All rights reserved.

引用

页码：5 / 14

页数：10

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