Asynchronous finite-time extended dissipative sliding mode control for semi-Markovian jump master-slave neural networks

被引:2
|
作者
Cheng, Guifang [1 ]
Liu, Hao [1 ]
机构
[1] Zhengzhou Univ, Sch Math & Stat, Zhengzhou 450001, Peoples R China
基金
中国国家自然科学基金;
关键词
Asynchronous controller; MSNNs; Sliding mode control; Finite-time contractive bound; Extended dissipative; OUTPUT-FEEDBACK CONTROL; EVENT-TRIGGERED CONTROL; SYNCHRONIZATION; SYSTEMS; STABILITY;
D O I
10.1016/j.chaos.2024.114457
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
This paper aims to investigate the finite -time extended dissipative asynchronous sliding mode control (SMC) on semi-Markovian jump master-slave neural networks (MSNNs) subject to event -triggering scheme (ETS) and packet dropout. Considering ETS, packet dropout and network -induced delays, the asynchronous finitetime SMC which is more realistic is designed. Sufficient conditions are obtained that closed -loop system is extended dissipative stochastic finite -time bound. Meantime, we present novel results for closed -loop system on extended dissipative stochastic finite -time contractive bound. Finally, the biological neural network is presented to illustrate the validness of methods.
引用
收藏
页数:11
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