Trajectory Tracking of Complex Dynamical Network for Chaos Synchronization Using Recurrent Neural Networks

Jose P. Perez, Joel Perez Padron, Angel Flores H., Martha S. Lopez de la Fuente


In this paper the problem of trajectory tracking is studied. Based on the Lyapunov theory, a control law that achieves the global asymptotic stability of the tracking error between a fractional recurrent neural network and the state of each single node of a fractional complex dynamical network is obtained. To illustrate the analytic results we present a tracking simulation of a simple network with four different nodes and five non-uniform links.


Fractional Complex Dynamical Systems, Trajectory Tracking, Lyapunov Theory, Control Law

Full Text: PDF