Generalization Backstepping Method Based on Stabilization of Parameters Perturbation Lu Chaos Using Adaptive Neuro-Fuzzy Inference System

Abstract

This study deals with the control and synchronization chaos using Generalized Backstepping Method (GBM). This new method to control nonlinear systems was called generalized backstepping method because of its similarity to Backstepping Method (BM) but its more abilities to control systems than it. GBM could achieve better performance than BM in respect of lower signal control, short settling time and overshoot, control ability of MIMO systems and non strictly feedback systems. GBM consists of parameters which accept positive values. The parameters are usually chosen optional. The system responded differently for each value. This paper introduce a novel adaptive neuro fuzzy control method which trained by different error data to achieve optimal parameters. So with optimal parameters controller can stabilize the Lu chaos in much quicker than GBM.