Complex Dynamical Network Control for Trajectory Tracking Using Delayed Recurrent Neural Networks
José P. Pérez, Joel Pérez Padron, Angel Flores Hemandez, Santiago Arroyo · Mathematical Problems in Engineering · 2014
In this paper, the problem of trajectory tracking is studied. Based on the V‐stability and Lyapunov theory, a control law that achieves the global asymptotic stability of the tracking error between a delayed recurrent neural network and a complex dynamical network is obtained. To illustrate the analytic results, we present a tracking simulation of a dynamical network with each node being just one Lorenz’s dynamical system and three identical Chen’s dynamical systems.