Robust adaptive control for a class of switched nonlinear systems with unmodeled dynamics

An adaptive neural network control scheme is proposed for a class of nonlinear switched systems with unmodeled dynamics in pure-feedback form. The design is based on the dynamic surface technique, the approximation capability of neural networks and the dwell-time approach. The design makes the approach of dynamic surface control be extended to the nonlinear switched system with unmodeled dynamics, and relaxes the extent of application of the approach of dynamic surface control. Compared with the existing literature, the proposed approach relaxes the requirements of the system. And the explosion of complexity in traditional backstepping design caused by repeated differentiations of virtual control is avoided. By theoretical analysis, the closed-loop control system is shown to be semi-globally uniformly ultimately bounded.