Paper Info
Title
Decentralized Adaptive Event-Triggered Synchronization of Neutral Neural Networks with Time-Varying Delays
Abstract
In this work, the adaptive event-triggered synchronization in a class of master–slave neutral neural networks with time-varying delay is studied. The design of decentralized event-triggered scheme is proposed, which only utilizes local available information to determine the released instants from multiple sensors to a centralized controller. Different from existing ones, the triggering thresholds depend on real-time performance of controlled system. Together with some novel Lyapunov terms, an augmented Lyapunov–Krasovskii functional is constructed, in which the interconnection between time delays can be fully utilized. In particular, a less conservative condition on controller gain is obtained in terms of linear matrix inequalities. Finally, the derived results are verified by resorting to two numerical examples.
Year
DOI
Venue
2019
10.1007/s00034-018-0889-2
Circuits, Systems, and Signal Processing
Keywords
Field
DocType
Neutral neural networks,Adaptive event-triggered scheme,Synchronization,Time-varying delay
Lyapunov function,Control theory,Synchronization,Matrix (mathematics),Control theory,Event triggered,Artificial neural network,Interconnection,Multiple sensors,Mathematics
Journal
Volume
Issue
ISSN
38
2
1531-5878
Citations 
PageRank 
References 
1
0.35
22
Authors
4
Name
Order
Citations
PageRank
Tao Li131526.00
Yaobao Yu210.35
Ting Wang3725120.28
Shu-Min Fei4115096.93