Open AccessImproved robust H ∞ exponential mean square stabilization for uncertain Markov jump delay systems based on memory‐state feedback control
Author(s) -
Wang Jie,
Zhuang Guangming,
Xia Jianwei,
Zhang Huasheng,
Sun Wei
Publication year - 2021
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/cth2.12066
Subject(s) - control theory (sociology) , controller (irrigation) , markov chain , exponential function , state (computer science) , jump , full state feedback , mathematics , linear matrix inequality , exponential stability , robustness (evolution) , computer science , control (management) , mathematical optimization , algorithm , nonlinear system , artificial intelligence , statistics , mathematical analysis , physics , quantum mechanics , biochemistry , chemistry , gene , agronomy , biology
This paper investigates the problem of robust H ∞ exponential mean square stabilisation for uncertain Markov jump systems with time‐varying and mode‐dependent delays based on memory‐state feedback control. Attention is focused on the design of memory‐state feedback controller for uncertain Markov jump systems with time‐varying and mode‐dependent delays such that the closed‐loop uncertain Markov jump systems satisfies robust H ∞ exponential mean square stability. The improved conditions for the solvability of the memory‐state feedback control problem are obtained via designing mode‐dependent and delay‐dependent L‐K functional. The desired memory‐state feedback controller is given by using linear matrix inequalities. Two simulation examples including a numerical example and a practical example of the industrial non‐isothermal continuous stirred tank reactor are used to demonstrate the effectiveness and usefulness of the delayed feedback control technique that this paper proposes.