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Double-quantized-based H∞ tracking control of T-S fuzzy semi-Markovian jump systems with adaptive event-triggered.

Authors :
Yuxin Lou
Mengzhuo Luo
Jun Cheng
Xin Wang
Kaibo Shi
Source :
AIMS Mathematics; 2023, Vol. 8 Issue 3, p6942-6969, 28p
Publication Year :
2023

Abstract

This paper investigates the issue of asynchronous H∞ tracking control for nonlinear semi-Markovian jump systems (SMJSs) based on the T-S fuzzy model. Firstly, in order to improve the performance of network control systems (NCSs) and the efficiency of data transmission, this paper adopts a double quantization strategy which quantifies the input and output of the controllers. Secondly, for the purpose of reducing the burden of network communication, an adaptive event-triggered mechanism (AETM) is adopted. Thirdly, due to the influence of network-induce delay, the system mode information can not be transmitted to the controller synchronously, thus, a continuous-time hidden Markov model (HMM) is established to describe the asynchronous phenomenon between the system and the controller. Additionally, with the help of some improved Lyapunov-Krasovski (L-K) functions with fuzzy basis, some sufficient criteria are derived to co-guarantee the state stability and the H∞ performance for the closed-loop tracking control system. Finally, a numerical example and a practical example are given to verify the effectiveness of designed mentality. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
24736988
Volume :
8
Issue :
3
Database :
Complementary Index
Journal :
AIMS Mathematics
Publication Type :
Academic Journal
Accession number :
161541046
Full Text :
https://doi.org/10.3934/math.2023351