@article{Lou2023, 
author = {Yuxin Lou and Mengzhuo Luo and Jun Cheng and Xin Wang and Kaibo Shi},
title = {Double-quantized-based        H          ∞       tracking control of T-S fuzzy semi-Markovian jump systems with adaptive event-triggered},
year = {2023},
journal = {AIMS Mathematics},
volume = {8},
number = {3},
pages = {6942-6969},
keywords = {tracking control, adaptive event-triggered mechanism, fuzzy semi-Markovian jump systems, asynchronous H∞ control, double quantization},
url = {https://www.sciopen.com/article/10.3934/math.2023351},
doi = {10.3934/math.2023351},
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.}
}