Finite-time decentralized event-triggered state estimation for coupled neural networks under unreliable Markovian network against mixed cyberattacks  

作　　者：Xiulin Wang Youzhi Cai Feng Li 汪修林;蔡有志;李峰(School of Electrical and Information Engineering,Anhui University of Technology,Maanshan 243032,China)

机构地区：[1]School of Electrical and Information Engineering,Anhui University of Technology,Maanshan 243032,China

出　　处：《Chinese Physics B》2024年第11期175-183,共9页中国物理B（英文版）

基　　金：Project supported by the National Natural Science Foundation of China(Grant No.62303016);the Research and Development Project of Engineering Research Center of Biofilm Water Purification and Utilization Technology of the Ministry of Education of China(Grant No.BWPU2023ZY02);the University Synergy Innovation Program of Anhui Province,China(Grant No.GXXT-2023-020);the Key Project of Natural Science Research in Universities of Anhui Province,China(Grant No.2024AH050171).

摘　　要：This article investigates the issue of finite-time state estimation in coupled neural networks under random mixed cyberattacks,in which the Markov process is used to model the mixed cyberattacks.To optimize the utilization of channel resources,a decentralized event-triggered mechanism is adopted during the information transmission.By establishing the augmentation system and constructing the Lyapunov function,sufficient conditions are obtained for the system to be finite-time bounded and satisfy the H_(∞ )performance index.Then,under these conditions,a suitable state estimator gain is obtained.Finally,the feasibility of the method is verified by a given illustrative example.

关 键 词：Markov jump systems coupled neural networks decentralized event-triggered mechanism finite-time state estimation 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]