Interval type-2 fuzzy filtering for singularly perturbed hidden Markov jump systems with general probabilities

This paper investigates the H∞ filtering problem for discrete-time nonlinear singularly perturbed Markov jump systems with hidden modes and general probabilities. An interval type-2 T-S fuzzy model is adopted to capture the nonlinearities and membership-function uncertainties, and a unified hidden Markov model-based framework is established to describe the mismatch between the true mode and the observed mode. Within this framework, both the transition probability matrix and the observation probability matrix are allowed to include known, uncertain, and unknown entries. An observation-mode-dependent interval type-2 fuzzy filter is developed, and sufficient membership-function-dependent LMI conditions are derived to ensure stochastic stability and a prescribed H∞ performance. The effectiveness of the proposed method is finally demonstrated by a tunnel-diode circuit example and a numerical example.

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Publication Details

Journal
International Journal of Systems Science
Published
2026-08-18
DOI
https://doi.org/10.1080/00207721.2026.2710894
Primary Topic
Stability and Control of Uncertain Systems
Type
article
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article

Interval type-2 fuzzy filtering for singularly perturbed hidden Markov jump systems with general probabilities

Guanqi Wang, Youzhi Cai
International Journal of Systems Science
Stability and Control of Uncertain Systems
article

Interval type-2 fuzzy filtering for singularly perturbed hidden Markov jump systems with general probabilities

Guanqi Wang, Youzhi Cai
article en

Abstract

This paper investigates the H∞ filtering problem for discrete-time nonlinear singularly perturbed Markov jump systems with hidden modes and general probabilities. An interval type-2 T-S fuzzy model is adopted to capture the nonlinearities and membership-function uncertainties, and a unified hidden Markov model-based framework is established to describe the mismatch between the true mode and the observed mode. Within this framework, both the transition probability matrix and the observation probability matrix are allowed to include known, uncertain, and unknown entries. An observation-mode-dependent interval type-2 fuzzy filter is developed, and sufficient membership-function-dependent LMI conditions are derived to ensure stochastic stability and a prescribed H∞ performance. The effectiveness of the proposed method is finally demonstrated by a tunnel-diode circuit example and a numerical example.

International Journal of Systems Science
Nanjing University of Science and Technology (CN)
Openalex Percentile: Top 13%
Stability and Control of Uncertain Systems
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