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Stability and Filtering for Delayed Discrete-Time T-S Fuzzy Systems via Membership-Dependent Approaches

Wenhu Chen, Chuan‐Ke Zhang, Zhou-Zhou Liu, Leimin Wang, Yong He

2024IEEE Transactions on Fuzzy Systems11 citationsDOI

Abstract

The stability and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\mathcal {H}}_\infty$</tex-math></inline-formula> filtering for delayed discrete-time T-S fuzzy systems are studied in this article. The primary objective is to obtain less conservative and more effective analysis and design methods by exploring a combination of the characteristics of T-S fuzzy systems and the delay-dependent methods. First, as the first step of the Lyapunov–Krasovskii functional (LKF) method, a membership-dependent (MD) LKF with delay-product-type term is established to contain more delay and membership function information. Then, to obtain the negative definite condition of the forward difference of the constructed functional, an MD-matrix-separation-based inequality is developed to obtain tighter estimations for the augmented summation terms and an MD-variable-augmented-based free-weighting matrix method is proposed to avoid the generation of delay-dependent nonlinear terms. Based on the abovementioned methods, a less conservative stability criterion and an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\mathcal {H}}_\infty$</tex-math></inline-formula> fuzzy filter design method are proposed. Finally, the merits of the proposed methods are verified via two examples.

Topics & Concepts

Stability (learning theory)Fuzzy logicFuzzy control systemDiscrete time and continuous timeComputer scienceFuzzy setMathematicsControl theory (sociology)Artificial intelligenceStatisticsMachine learningControl (management)Mathematical Control Systems and AnalysisCybersecurity and Information Systems
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