PID Control Law for Trajectory Tracking Error Using Time-Delay Adaptive Neural Networks for Chaos Synchronization

Authors

  • Joel Perez Padron Universidad Autonoma de Nuevo Leon
  • Jose Paz Perez Padron Universidad Autonoma de Nuevo Leon

DOI:

https://doi.org/10.13053/cys-19-2-1908

Keywords:

Lyapunov-Krasovskii function stability, chaos synchronization, trajectory tracking, time-delay adaptive neural networks, PID control.

Abstract

This paper presents an application of Time-Delay adaptive neural networks based on a dynamic neural network for trajectory tracking of unknown nonlinear plants. Our approach is based on two main methodologies: the first one employs Time-Delay neural networks and Lyapunov-Krasovskii functions and the second one is Proportional-Integral-Derivative (PID) control for nonlinear systems. The proposed controller structure is composed of a neural identifier and a control law defined by using the PID approach. The new control scheme is applied via simulations to Chaos Synchronization. Experimental results have shown the usefulness of the proposed approach for Chaos Production. To verify the analytical results, an example of a dynamical network is simulated and a theorem is proposed to ensure the tracking of the nonlinear system.

Author Biographies

Joel Perez Padron, 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.

Jose Paz Perez Padron, Universidad Autonoma de Nuevo Leon

Jose Paz Perez Padron obtained his B.Sc. degree in Mathematics in 1990, from the Faculty of Physical and Mathematical Sciences, a Master’s degree in Electrical Engineering with specialization in Control in 1999, from the Faculty of Mechanical and Electrical Engineering, and a Ph.D. in Science in Electrical Engineering in 2004, from the Cinvestav-Gdl.

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Published

2015-06-01

Issue

Vol. 19 No. 2 (2015): 19(2) April-June 2015

Section

Articles

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