Strict dissipativity synchronization for delayed static neural networks: An event-triggered scheme. (September 2021)

• Record Type: Journal Article
• Authors: Vadivel, R.; Hammachukiattikul, P.; Gunasekaran, Nallappan; Saravanakumar, R.; Dutta, Hemen
• Is Part Of: Chaos, solitons and fractals. Volume 150(2021)
• Publication Date: 2021-09
• Subjects: Dissipativity -- Event-triggered control -- Lyapunov-Krasovskii functional -- Static neural networks -- Synchronization; Chaotic behavior in systems -- Periodicals; Solitons -- Periodicals; Fractals -- Periodicals; Chaotic behavior in systems; Fractals; Solitons; Periodicals; 003.7
• DOI: 10.1016/j.chaos.2021.111212
• Languages: English
• ISSNs: 0960-0779

Abstract

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.