Event-triggered hybrid impulsive control for synchronization of memristive neural networks

作     者：Yijun ZHANG Yuangui BAO Yijun ZHANG;Yuangui BAO

作者机构：Automation SchoolNanjing University of Science and Technology 

出 版 物：《Science China(Information Sciences)》 (中国科学:信息科学(英文版))

年 卷 期：2020年第63卷第5期

页      面：75-86页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0802[工学-机械工程] 0811[工学-控制科学与工程] 080201[工学-机械制造及其自动化] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by National Natural Science Foundation of China (Grant No. 61973166) Fundamental Research Funds for the Central Universities (Grant No. 30919011409) 

主　　题：event-triggered synchronization memristive neural networks impulsive control Zeno behavior 

摘      要：This paper is concerned with the complete synchronization of memristive neural networks(MNNs) with time-varying delays. An event-triggered hybrid state feedback and impulsive controller is designed to save the limited system communication resources, and parameter mismatch is considered in the control design process. Based on the Lyapunov functional approach and the comparison principle for impulsive systems, a sufficient synchronization criterion is developed to derive the master MNN and response ***, under the event-triggered mechanism there exists a positive lower bound for inter-execution time, which implies the avoidance of Zeno behavior. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed synchronization design methods.