Open AccessFinite‐time robust fuzzy control for non‐linear Markov jump systems under aperiodic sampling and actuator constraints
Author(s) -
Xu Shidong,
Sun Guanghui,
Li Zhan,
Zheng Hui
Publication year - 2017
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2016.1609
Subject(s) - control theory (sociology) , aperiodic graph , mathematics , fuzzy logic , controller (irrigation) , actuator , piecewise , mathematical optimization , fuzzy control system , markov chain , computer science , control (management) , artificial intelligence , statistics , mathematical analysis , combinatorics , agronomy , biology
This study investigates the fuzzy control problem for a class of non‐linear Markov jump systems with sampled‐data inputs and actuator constraints over a finite‐time interval. Takagi–Sugeno (T–S) fuzzy models are employed to approximate the non‐linearity. The partly known transition probability matrix consisting of known, uncertain, and unknown elements is considered. The asynchronous errors of the membership functions induced by aperiodic sampling are taken care of to avoid conservative results. The objective is to procure a sampled‐data fuzzy controller such that the resulting closed‐loop system is finite‐time bounded and a prescribed performance index is guaranteed simultaneously. By establishing a new piecewise Lyapunov–Krasovskii functional and utilising convex optimisation technique, a novel set of sufficient conditions for the existence of anticipated sampled‐data controller are developed. Finally, two illustrative examples are presented to prove the effectiveness of the proposed approaches.