Strict dissipativity synchronization for delayed static neural networks: An event-triggered scheme

R. Vadivel, P. Hammachukiattikul, Nallappan Gunasekaran, R. Saravanakumar and Hemen Dutta

Chaos, Solitons & Fractals, 2021, vol. 150, issue C

Abstract: This article addresses the investigation of strict dissipativity synchronization for a class of static neural networks under an event-triggered scheme. An event-triggered scheme is recommended, it can upgrade the exhibition of system dynamics and diminishes the network communication burden at the same time. Firstly, an appropriate Lyapunov-Krasovskii functional (LKF) with double and triple integral terms with the details on both lower and upper bounds of the delay is completely designed. Secondly, under the single and double Auxillary function-based integral inequalities (SAFBII and DAFBII, respectively) and generalized free weight matrix approach, a new class of delay-dependent adequate condition is proposed, so that the error system is (Q,S,R)−γ− strict dissipative. A resilient distributed event-triggered control scheme is developed by this criterion in terms of linear matrix inequalities (LMIs). At last, simulation examples are provided to demonstrate the performance of the derived results.

Keywords: Dissipativity; Event-triggered control; Lyapunov-Krasovskii functional; Static neural networks; Synchronization (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:150:y:2021:i:c:s096007792100566x

DOI: 10.1016/j.chaos.2021.111212

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