Interval Type-2 Fuzzy $\mathcal{H}_{\infty}$ Filtering for Singularly Perturbed Jumping Systems Based on Hidden Markov Model

This study investigates the fuzzy filtering problem for mode-constrained nonlinear Markov jump singularly perturbed systems and discusses its application in electronic circuits. The research initially employs an interval type-2 fuzzy modeling approach to address inherent system uncertainties and nonlinear characteristics. Building upon this foundation, an interval type-2 fuzzy filter correlated with observation mode yet independent of singularly perturbed parameters is constructed through integration of hidden Markov model and non-parallel distributed compensation technique. To simultaneously guarantee stochastic stability and achieve prescribed <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathcal{H}_{\infty}$</tex> performance specifications for the filtering error system, several membership-functiondependent sufficient conditions are derived. The introduction of relax matrices incorporating dual adjustable parameters for calculating the fuzzy filter gains. Ultimately, the effectiveness of developed methodology is validated by an electronic circuit model.

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Publication Details

Published
2025-07-04
DOI
https://doi.org/10.1109/fasta65681.2025.11138229
Primary Topic
Fuzzy Systems and Optimization
Type
article
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article

Interval Type-2 Fuzzy $\mathcal{H}_{\infty}$ Filtering for Singularly Perturbed Jumping Systems Based on Hidden Markov Model

Guanqi Wang, Chenxiao Cai
Fuzzy Systems and Optimization
article

Interval Type-2 Fuzzy $\mathcal{H}_{\infty}$ Filtering for Singularly Perturbed Jumping Systems Based on Hidden Markov Model

Guanqi Wang, Chenxiao Cai
article en

Abstract

This study investigates the fuzzy filtering problem for mode-constrained nonlinear Markov jump singularly perturbed systems and discusses its application in electronic circuits. The research initially employs an interval type-2 fuzzy modeling approach to address inherent system uncertainties and nonlinear characteristics. Building upon this foundation, an interval type-2 fuzzy filter correlated with observation mode yet independent of singularly perturbed parameters is constructed through integration of hidden Markov model and non-parallel distributed compensation technique. To simultaneously guarantee stochastic stability and achieve prescribed <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathcal{H}_{\infty}$</tex> performance specifications for the filtering error system, several membership-functiondependent sufficient conditions are derived. The introduction of relax matrices incorporating dual adjustable parameters for calculating the fuzzy filter gains. Ultimately, the effectiveness of developed methodology is validated by an electronic circuit model.

Nanjing University of Science and Technology (CN)
Openalex Percentile: Top 77%
Fuzzy Systems and Optimization
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