Synchronization of complex networks with nonidentical nodes via discrete-time neural inverse optimal pinning control

Abstract

In this paper, discrete-time inverse optimal pinning controller based on a neural model for synchronization of uncertain complex networks with nonidentical nodes is presented. For identification a Recurrent High-Order Neural Network (RHONN) trained with an Extended Kalman Filter (EKF) is used. The RHONN identifies a satisfactory model, which is robust in presence of disturbances and parameter variations; for synchronization an discrete-time inverse optimal controller is applied. An illustrative example composed by a network of eight different chaotic nodes, allows to verify the control scheme performance, via simulations.