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Filtering for Discrete-Time Takagi–Sugeno Fuzzy Nonhomogeneous Markov Jump Systems With Quantization Effects

Mingang Hua, Yang‐Yang Qian, Feiqi Deng, Juntao Fei, Pei Cheng, Hua Chen

2020IEEE Transactions on Cybernetics61 citationsDOI

Abstract

This article deals with the problem of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$l_{2}-l_{\infty }$ </tex-math></inline-formula> filtering for discrete-time Takagi–Sugeno fuzzy nonhomogeneous Markov jump systems with quantization effects, respectively. The time-varying transition probabilities are in a polytope set. To reduce conservativeness, a mode-dependent logarithmic quantizer is considered in this article. Based on the fuzzy-rule-dependent Lyapunov function, sufficient conditions are given such that the filtering error system is stochastically stable and has a prescribed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> or <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$l_{2}-l_{\infty }$ </tex-math></inline-formula> performance index, respectively. Finally, a practical example is provided to illustrate the effectiveness of the proposed fuzzy filter design methods.

Topics & Concepts

Discrete time and continuous timeMathematicsFuzzy logicJumpControl theory (sociology)Markov chainComputer scienceApplied mathematicsArtificial intelligenceStatisticsControl (management)PhysicsQuantum mechanicsFuzzy Logic and Control SystemsStability and Control of Uncertain SystemsChaos control and synchronization