Adaptive dynamic surface control for perturbed nonlinear systems

In this paper, an adaptive neural network control is proposed for a class of nonlinear systems in pure feedback form with unknown system functions and uncertain disturbances. The design is based on the backstepping method, the dynamic surface control technique and the approximation capability of neural networks and the Lyapunov function of integral type. Compared with the existing literature, the proposed approach contains only one adaptive parameter that needs to be updated online. By theoretical analysis, the closed-loop control system is shown to be semi-globally uniformly ultimately bounded. Finally, simulation results verify the effectiveness of the proposed approach.