RBF network with sliding-mode control for chaos systems

Abstract

In this paper a robust intelligent RBF neural network tracking control system combined with a distance-based sliding-mode control technique is proposed for a class of chaos systems. The proposed adaptive control scheme is developed for a class of chaotic systems with unknown bounded uncertainties. The adaptation laws are derived using a Lyapunov stability analysis, so that both system tracking stability and error convergence can be guaranteed in the closed-loop system. It is used to demonstrate the effectiveness and performance of the proposed robust control technique. © 2011 Springer-Verlag.