Paper Info
Title
Event-triggered H∞ anti-synchronisation for delayed neural networks with discontinuous neuron activations via non-fragile control strategy
Abstract
This paper treats of the global event-triggered anti-synchronisation issue for discontinuous neural networks with the mixed time-varying delays and random feedback gain fluctuation via non-fragile control strategy. The random gain uncertainties are described by stochastic variables satisfying the Bernoulli distribution. Firstly, the novel hybrid controllers, which are composed of the non-fragile controller and the event-triggered controller, are designed. Then, based on Clarke's non-smooth analysis theory, general free-weighting matrix method, the Lyapunov-Krasovskii functional approach and Wirtinger-based multiple integral inequality analysis technology, the global event-triggered non-fragile anti-synchronisation conditions are established in terms of linear matrix inequalities (LMIs). In addition, under the considered external disturbance, the conditions with respect to the global event-triggered non-fragile anti-synchronisation are also addressed in forms of LMIs. Finally, two illustrative examples are provided to verify the effectiveness of the designed event-triggered non-fragile control scheme and the validity of theoretical results.
Year
DOI
Venue
2019
10.1080/09540091.2019.1604628
CONNECTION SCIENCE
Keywords
Field
DocType
Discontinuous neural networks,non-fragile anti-synchronisation,H-infinity anti-synchronisation,mixed time-varying delays,event-triggered control scheme,Wiritinger-based multiple integral inequality
Bernoulli distribution,Control theory,Synchronization,Functional approach,Computer science,Matrix (mathematics),Control theory,Matrix method,Artificial intelligence,Multiple integral,Artificial neural network
Journal
Volume
Issue
ISSN
31.0
4
0954-0091
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Min Liu15616.44
Huaiqin Wu2597.92
Jinde Cao311399733.03
Yanning Wang493.00