Finite-time and sampled-data synchronization of complex dynamical networks subject to average dwell-time switching signal. (May 2022)

• Record Type: Journal Article
• Authors: Gunasekaran, Nallappan; Ali, M. Syed; Arik, Sabri; Ghaffar, H.I. Abdul; Diab, Ahmed A. Zaki
• Is Part Of: Neural networks. Volume 149(2022)
• Page Start: 137
• Page End: 145
• Publication Date: 2022-05
• Subjects: Average dwell-time -- Complex dynamical networks -- Finite-time boundedness -- Lyapunov method -- Sampled-data control -- Switching signal; Neural computers -- Periodicals; Neural networks (Computer science) -- Periodicals; Neural networks (Neurobiology) -- Periodicals; Nervous System -- Periodicals; Ordinateurs neuronaux -- Périodiques; Réseaux neuronaux (Informatique) -- Périodiques; Réseaux neuronaux (Neurobiologie) -- Périodiques; Neural computers; Neural networks (Computer science); Neural networks (Neurobiology); Periodicals; 006.32
• DOI: 10.1016/j.neunet.2022.02.013
• Languages: English
• ISSNs: 0893-6080

Abstract

Abstract: This study deals with the finite-time synchronization problem of a class of switched complex dynamical networks (CDNs) with distributed coupling delays via sampled-data control. First, the dynamical model is studied with coupling delays in more detail. The sampling system is then converted to a continuous time-delay system using an input delay technique. We obtain some unique and less conservative criteria on exponential stability using the Lyapunov–Krasovskii functional (LKF), which is generated with a Kronecker product, linear matrix inequalities (LMIs), and integral inequality. Furthermore, some sufficient criteria are derived by an average dwell-time method and determine the finite-time boundedness of CDNs with switching signal. The proposed sufficient conditions can be represented in the form of LMIs. Finally, numerical examples are given to show that the suggested strategy is feasible.