Controlling the chaotic discrete-Henon system using a feedforward neural network with an adaptive learning rate

Abstract

This paper proposes a feedforward neural network-based control scheme to control the chaotic trajectories of a discrete-Henon map in order to stay within an acceptable distance from the stable fixed point. An adaptive learning back propagation algorithm with online training is employed to improve the effectiveness of the proposed method. The simulation study carried in the discrete-Henon system verifies the validity of the proposed control system.