Adaptive neural network sliding mode control for a class of non-affine nonlinear systems with pure-feedback prototype

This paper studies non-affine nonlinear systems with pure-feedback prototype, the nonlinear systems identified by neural network technique, the weighting coefficients of neural network are adjusted by adaptive technique, the adaptive neural network sliding mode controller is designed based on Lyapunov stability theory, in order to achieved uniformly ultimately boundedness of the closed-loop systems. Finally, two numerical examples are given to illustrate the effectiveness of the proposed theory.