A new method of fault estimation and tolerant control for fuzzy systems against time-varying delay

In the study, the issues of observer-based fault estimation (FE) as well as active fault-tolerant control (FTC) are considered based on a series of Takagi–Sugeno (T–S) fuzzy models against time-varying delay. Utilizing these obtained (k−1)th messages, a new k-step T–S fuzzy fast adaptive FE method i...

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Bibliographic Details
Published inNonlinear analysis. Hybrid systems Vol. 38; p. 100942
Main Authors Sun, Shaoxin, Wang, Yingchun, Zhang, Huaguang, Xie, Xiangpeng
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.11.2020
Subjects
Controller
Fault estimation (FE)
Fuzzy Lyapunov–Krasovskii functional
Takagi–Sugeno (T–S) fuzzy systems
Time-varying delay
Takagi–Sugeno (T–S) fuzzy systems
Fault estimation (FE)
Controller
Fuzzy Lyapunov–Krasovskii functional
Time-varying delay
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Summary:In the study, the issues of observer-based fault estimation (FE) as well as active fault-tolerant control (FTC) are considered based on a series of Takagi–Sugeno (T–S) fuzzy models against time-varying delay. Utilizing these obtained (k−1)th messages, a new k-step T–S fuzzy fast adaptive FE method is suggested to construct this observer. And a full-order controller is suggested to make the closed-loop system stable by compensating this fault effect. In contrast to the existing study works, the addressed controller can be carried out in a wider application scope. A fuzzy Lyapunov–Krasovskii functional method is utilized to analyze the stability of the closed-loop system. Meanwhile, sufficient stability conditions are proposed through linear matrix inequalities (LMIs) calculated by Matlab toolbox. Finally, the merits of this suggested approach are demonstrated via two simulation examples.
ISSN:1751-570X
DOI:10.1016/j.nahs.2020.100942