Distributed dynamic event-based finite-time dissipative synchronization control for semi-Markov switched fuzzy cyber-physical systems against random packet losses

作     者：伍锡如 张煜翀 张畑畑 张斌磊 Xiru Wu;Yuchong Zhang;Tiantian Zhang;Binlei Zhang

作者机构：School of Electronic Engineering and AutomationGuilin University of Electronic TechnologyGuilin 541004China 

出 版 物：《Chinese Physics B》 (中国物理B（英文版）)

年 卷 期：2023年第32卷第10期

页      面：328-342页

核心收录：

学科分类：0711[理学-系统科学] 07[理学] 08[工学] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 071102[理学-系统分析与集成] 081103[工学-系统工程] 

基　　金：Project supported by the National Natural Science Foundation of China (Grant No. 62263005) Guangxi Natural Science Foundation (Grant No. 2020GXNSFDA238029) Laboratory of AI and Information Processing (Hechi University), Education Department of Guangxi Zhuang Autonomous Region (Grant No. 2022GXZDSY004) Innovation Project of Guangxi Graduate Education (Grant No. YCSW2023298) Innovation Project of GUET Graduate Education (Grant Nos. 2022YCXS149 and 2022YCXS155) 

主　　题：cyber-physical systems finite-time synchronization distributed dynamic event-triggered mechanism random packet losses 

摘      要：This paper is concerned with the finite-time dissipative synchronization control problem of semi-Markov switched cyber-physical systems in the presence of packet losses, which is constructed by the Takagi–Sugeno fuzzy model. To save the network communication burden, a distributed dynamic event-triggered mechanism is developed to restrain the information update. Besides, random packet dropouts following the Bernoulli distribution are assumed to occur in sensor to controller channels, where the triggered control input is analyzed via an equivalent method containing a new stochastic variable. By establishing the mode-dependent Lyapunov–Krasovskii functional with augmented terms, the finite-time boundness of the error system limited to strict dissipativity is studied. As a result of the help of an extended reciprocally convex matrix inequality technique, less conservative criteria in terms of linear matrix inequalities are deduced to calculate the desired control gains. Finally, two examples in regard to practical systems are provided to display the effectiveness of the proposed theory.