Analysis and Controller Design for Parameter Varying T-S Fuzzy Systems with Markov Jump

In this paper, we investigate a novel T-S fuzzy parameter varying system with Markov jump, in which parameters depend not only on a Markov chain but also on linear parameter varying elements that take values in convex polytopic sets. Stable conditions and the gain-scheduling controller design method for this system are obtained. Applying Lyapunov function depending on the operation mode and full block S-procedure lemma, we obtain stochastic stabilization conditions. We find that this novel system has two distinct advantages. On the one hand, it inherits the advantages of traditional T-S fuzzy systems in handling nonlinear objects under the frame of T-S fuzzy systems; on the other, it obtains the advantages of dealing with time-varying characteristics from the point of linear parameter varying (LPV) systems. Finally, the theory results are illustrated via numerical simulation.

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Publication Details

Journal
Mathematics
Published
2024-08-31
DOI
https://doi.org/10.3390/math12172721
Citations
2
Primary Topic
Fuzzy Logic and Control Systems
Type
article
Field-Weighted Citation Impact
0.69

Funders

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article

Analysis and Controller Design for Parameter Varying T-S Fuzzy Systems with Markov Jump

Na Min, Hongyang Zhang
2 citations
Mathematics
Fuzzy Logic and Control Systems
0.69
article

Analysis and Controller Design for Parameter Varying T-S Fuzzy Systems with Markov Jump

Na Min, Hongyang Zhang
article en
2 citations

Abstract

In this paper, we investigate a novel T-S fuzzy parameter varying system with Markov jump, in which parameters depend not only on a Markov chain but also on linear parameter varying elements that take values in convex polytopic sets. Stable conditions and the gain-scheduling controller design method for this system are obtained. Applying Lyapunov function depending on the operation mode and full block S-procedure lemma, we obtain stochastic stabilization conditions. We find that this novel system has two distinct advantages. On the one hand, it inherits the advantages of traditional T-S fuzzy systems in handling nonlinear objects under the frame of T-S fuzzy systems; on the other, it obtains the advantages of dealing with time-varying characteristics from the point of linear parameter varying (LPV) systems. Finally, the theory results are illustrated via numerical simulation.

MathematicsVol. 12(17)
Guangdong University of Technology (CN), Guangdong Polytechnic Normal University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 25%
Fuzzy Logic and Control Systems
0.69
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