Abstract

In this work, a neural impulsive pinning controller for a twenty-node dynamical discrete complex network is presented. The node dynamics of the network are all different types of discrete versions of chaotic attractors of three dimensions. Using the V-stability method, we propose a criterion for selecting nodes to design pinning control, in which only a small fraction of the nodes is locally controlled in order to stabilize the network states at zero. A discrete recurrent high order neural network (RHONN) trained with extended Kalman filter (EKF) is used to identify the dynamics of controlled nodes and synthesize the control law.

Highlights

  • In recent years, complex networks have been gaining more attention in the scientific community, with a wide range of applications, from computer science to sociology [1]

  • A technique developed for the control of complex dynamical networks is pinning control, which consists of controlling only a small fraction of nodes of a complex network [3]

  • Numerous studies have been published around this pinning control technique, of particular interest to this study is the one of V-stability [4], in which the stability problem for a complex network with different dynamics in its nodes is transformed to verify positive definiteness of an associated matrix

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Summary

Introduction

Complex networks have been gaining more attention in the scientific community, with a wide range of applications, from computer science to sociology [1]. There are many techniques in control theory that have been developed over the years in order to achieve stability around a given equilibrium point [2]. Using a particular method of control depends on the designer or the type of system that is being worked on. A technique developed for the control of complex dynamical networks is pinning control, which consists of controlling only a small fraction of nodes of a complex network [3]. Numerous studies have been published around this pinning control technique, of particular interest to this study is the one of V-stability [4], in which the stability problem for a complex network with different dynamics in its nodes is transformed to verify positive definiteness of an associated matrix

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