An auxiliary system discretization approach to Takagi-Sugeno fuzzy models

被引：5

作者：

Campos, Victor C. da S. ^{[1
]}

Braga, Marcio F. ^{[2
]}

Frezzatto, Luciano ^{[1
]}

机构：

[1] Univ Fed Minas Gerais UFMG, Dept Elect Engn, Av Antonio Carlos 6627, BR-31270901 Belo Horizonte, MG, Brazil

[2] Univ Fed Ouro Preto UFOP, Exact & Appl Sci Inst ICEA, Dept Elect Engn, Rua Trinta & Seis 115, BR-35931008 Joao Monlevade, MG, Brazil

来源：

FUZZY SETS AND SYSTEMS | 2022年 / 426卷

关键词：

Discretization; Nonlinear systems; Takagi-Sugeno fuzzy models; Observers; Linear matrix inequalities; NONLINEAR-SYSTEMS; STABILIZATION; STABILITY; FEEDBACK; DESIGN;

D O I：

10.1016/j.fss.2020.12.013

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This paper proposes a new procedure for discretizing nonlinear systems described by Takagi-Sugeno fuzzy models. The discretization procedure consists of obtaining a linear auxiliary system that approximates the Takagi-Sugeno model over a sampling instant. By discretizing this auxiliary system, a norm bounded uncertain linear discrete-time system is found, which is capable of representing the fuzzy model. This auxiliary system, as well as the norm bounded uncertainty, is found by solving an optimization problem with Linear Matrix Inequality (LMI) constraints. To illustrate the discretization procedure, a constant state observer is synthesized based on simple LMI conditions and then applied to a real nonlinear Chua's circuit. Additionally, a state-feedback controller based on our discretization approach is synthesized and we obtain larger maximum sampling periods than other tested strategies from the literature. (c) 2020 Elsevier B.V. All rights reserved.

引用

页码：94 / 105

页数：12

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