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Control for discrete-time fuzzy Markov jump systems with mode-dependent antecedent parts

Lixian Zhang, Ting Yang, Fen Wu

Year
2014
Citations
3

Abstract

This paper is concerned with the control problem for a class of discrete-time fuzzy Markov jump systems (MJSs). Unlike the common assumption in the existing literature, the antecedent parts of fuzzy rules are mode-dependent, i.e., the premise variables and/or their fuzzy partitions can be different in different modes. Based on a fuzzy-basis-dependent and mode-dependent Lyapunov function, the existence conditions of the desired mode-dependent state feedback controller are derived such that the closed-loop system is stochastically stable and achieves a guaranteed performance in the H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> sense. Two examples, including a practical example of robot arm, are used to demonstrate the applicability of the obtained theoretical results.

Keywords

Antecedent (behavioral psychology)Fuzzy logicFuzzy control systemControl theory (sociology)Controller (irrigation)Discrete time and continuous timeMode (computer interface)Markov chainComputer scienceMathematics

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