Adaptive Backstepping Control for a Class of Nonlinear Uncertain Systems using Fuzzy Neural Networks

In this study, an adaptive backstepping control scheme using fuzzy neural networks is proposed for a class of nonlinear uncertain systems. Two kinds of fuzzy neural networks (FNNs) are used to estimate the unknown system functions. According to the estimated value of the FNNs, the control input can be chosen by backstepping design procedures, and then the system output follows the desired trajectory. Based on the Lyapunov approach, the adaptive laws and stability analysis were obtained. Finally, computer simulation results are shown to demonstrate the performances of our approach.