Robust adaptive radial wavelet neural network control for chaotic systems using backstepping design

Abstract

This paper designs an adaptive and robustness backstepping control law to realize the control of Rossler-like systems of uncertainties. First, a wavelet network is used for the identification the nonlinear part of the system to change it into parametric model with parametric and structural uncertainties; Then, for the parameter uncertainties, an adaptive control law is designed to online estimate the unknown parameters; for the structural uncertainties, a robust control law is designed to make the system robustness. Finally, The effective of this methodology is illustrated by the simulation results.