Complex Dynamical Network Control for Trajectory Tracking Using Delayed Recurrent Neural Networks

Jose P. Perez, Joel Perez Padron, Angel Flores Hemandez and Santiago Arroyo

Mathematical Problems in Engineering, 2014, vol. 2014, 1-7

Abstract:

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.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:162610

DOI: 10.1155/2014/162610

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