Wavelet-neural-network-based backstepping control for chaotic systems

This paper proposes a wavelet-neural-network-based backstepping control (WNNBC) for the chaotic systems. The WNNBC is comprised of a neural backstepping controller and an adaptive robust controller. The neural backstepping controller containing a wavelet neural network identifier is the principal controller, and the adaptive robust controller is designed to achieve L₂ tracking performance with desired attenuation level. Finally, simulation results verify that the proposed WNNBC can achieve favorable tracking performance.