Improved criteria of sampled-data master-slave synchronization for chaotic neural networks with actuator saturation

Abstract

This paper investigates the sampled-data master-slave synchronization problem for chaotic neural networks with actuator saturation by constructing novel Lyapunov-Krasovskii functionals. The proposed functionals exploit the sampling interval from the recent sampling instant tk to the next sampling instant tk+1 by using the integral vectors ∫tkte(s)ds, 2t−tk∫tkt∫tkse(u)duds, ∫ttk+1e(s)ds, and 2tk+1−t∫ttk+1∫stk+1e(u)duds. Based on the proposed functionals, this paper derives sufficient criteria for the sampled-data master-slave synchronization of chaotic neural networks with actuator saturation represented using a dead zone nonlinearity. Also, the controller gain matrix of the sampled-data controller can be obtained by solving linear matrix inequalities (LMIs). The superiority and validity of the proposed criterion are verified through the numerical example obtained from the literature.