Adaptive Neuro-Fuzzy Control of Non-Affine Nonlinear Systems
In this paper, an adaptive neuro-fuzzy controller is investigated for a class of non-affine nonlinear systems. Firstly, rigorous description and quantification of the approximation error of the neuro-fuzzy controller are discussed. Then a novel updating algorithm to adapt the weights, centers, and widths of the neuro-fuzzy controller is presented based on Lyapunov stability theory. It is shown that the proposed design method is able to guarantee the stability of the closed-loop system and the convergence of the tracking error. Finally, simulation results illustrate the effectiveness of the proposed adaptive neuro-fuzzy control scheme