Fuzzy Control and Filtering for Nonlinear Singularly Perturbed Markov Jump Systems

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162

초록

This article addresses the H-infinity control and filtering problems for Markov jump singularly perturbed systems approximated by Takagi-Sugeno fuzzy models. The underlying transition probabilities (TPs) are assumed to vary randomly in a finite set, which is characterized by a higher level TP matrix. The mode- and variation-dependent fuzzy static outputfeedback controller (SOFC) and filter are designed, respectively, to fulfill the control and filtering purposes. To facilitate the fuzzy SOFC synthesis, the closed-loop system is transformed into a fuzzy piecewise-homogeneous Markov jump singularly perturbed descriptor system (MJSPDS) by descriptor representation. A rigorous proof of mean-square exponential admissibility for the resulting fuzzy MJSPDS is presented. The criterion ensuring the mean-square exponential stability of the fuzzy filtering error system is further formed based on similar procedures. By setting the specific forms of the related matrix variables, the solutions for the predesigned fuzzy SOFC and filter are furnished, respectively. Finally, feasibility and validities of the developed fuzzy control and filtering results are verified by two practical examples.

키워드

Filteringoutput-feedback controlpiecewise-homogeneous Markov jump systemsingularly perturbed system (SPS)Takagi-Sugeno fuzzy modelPOLE-PLACEMENT CONSTRAINTSOUTPUT-FEEDBACK CONTROLCONTROL DESIGNSTABILIZATIONSTABILITY
제목
Fuzzy Control and Filtering for Nonlinear Singularly Perturbed Markov Jump Systems
저자
Wang, YueyingAhn, Choon KiYan, HuaichengXie, Shaorong
DOI
10.1109/TCYB.2020.3004226
발행일
2021-01
유형
Article
저널명
IEEE Transactions on Cybernetics
51
1
페이지
297 ~ 308