Fractional Complex Dynamical Systems for Trajectory Tracking using Fractional Neural Network

Authors

  • Joel Perez P. Universidad Autonoma de Nuevo Leon

DOI:

https://doi.org/10.13053/cys-20-2-2201

Keywords:

Fractional complex dynamical systems, trajectory tracking, Lyapunov theory, control law.

Abstract

In this paper the problem of trajectory tracking is studied. Based on Lyapunov theory, a control law that achieves global asymptotic stability of the tracking error between a fractional recurrent neural network and the state of each single node of the 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.

Author Biography

Joel Perez P., Universidad Autonoma de Nuevo Leon

Joel Perez Padron obtained his B.Sc. degree in Mathematics in 1991, from the Faculty of Physical and Mathematical Sciences, a Master’s degree in Electrical Engineering with specialization in Control in 2001, from the Faculty of Mechanical and Electrical Engineering, and a Ph.D. in Industrial Physics Engineering with specialization in Control in 2008, from the Faculty of Physical and Mathematical Sciences of Nuevo Leon Autonomous University.

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Published

2016-06-25

Issue

Vol. 20 No. 2 (2016): 20-2 (2016)

Section

Articles

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