A radial basis function sliding mode controller for chaotic Lorenz system

Abstract

This Letter presents a novel method to controlling Lorenz chaos via an adaptive radial basis function sliding mode controller. The proposed scheme combines the advantages of the adaptive control, neural network and sliding mode control strategies without precise system model information. It has on-line learning ability to deal with the parametric uncertainty and disturbance by adjusting the control parameters. A sliding mode controller is designed via the Lyapunov stability theory in order to guarantee the high quality of the controlled system. The simulation results show that this method is feasible and effective for chaos control, and the robustness to parametric changes and extern disturbance is provided.