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Event-triggered synchronization for stochastic delayed neural networks: Passivity and passification case |
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| Authors: | R Vadivel P Hammachukiattikul Quanxin Zhu Nallappan Gunasekaran |
| Affiliation: | 1. Department of Mathematics, Faculty of Science and Technology, Phuket Rajabhat University, Phuket, Thailand
Contribution: Conceptualization, Methodology, Software;2. Department of Mathematics, Faculty of Science and Technology, Phuket Rajabhat University, Phuket, Thailand Contribution: Conceptualization, ?Investigation, Methodology, Software, Visualization;3. School of Mathematics and Statistics, Hunan Normal University, Changsha, China;4. Computational Intelligence Laboratory, Toyota Technological Institute, Aichi, Nagoya, Japan |
| Abstract: | This article investigates the event-triggered synchronization problem of stochastic neural networks under passivity and passification cases. For saving communication resources, an event-triggered approach is engaged in the design of synchronization for the delayed stochastic neural networks. To decrease network trouble, an event-triggered scheme is suggested between the sampler and communication network. A nonfragile event-triggered controller is intended to guarantee the finite-time stability of the subsequent closed-loop system. By applying the Lyapunov–Krasovkii functional (LKF) and the novel integral inequalities, a stability criteria for an interval-time varying delay error system ensure the designed controller can fulfill the necessities of passivity and passification performance. The desired control gain and event-triggered parameters are then found based on the linear matrix inequalities (LMIs). Finally, illustrative examples are given to show the benefits and validity of the desired control law. |
| Keywords: | event-triggered control Lyapunov–Krasovskii functional passivity stochastic neural networks synchronization |