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

被引:0
作者
Yijun Zhang
Yuangui Bao
机构
[1] Nanjing University of Science and Technology,Automation School
来源
Science China Information Sciences | 2020年 / 63卷
关键词
event-triggered; synchronization; memristive neural networks; impulsive control; Zeno behavior;
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学科分类号
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 MNN. Additionally, 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.
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