Adaptive neural switching control with average dwell-time technique

In this paper, an adaptive neural control problem for a class of switched nonlinear systems with unknown control gain is presented. RBF neural networks (RBF NNs) are used as a tool for modeling the unknown control law up to a small error tolerance. Based on the proposed control scheme with average dwell-time technique, it´s proved that the resulting closed-loop system is asymptotically Lyapunov stable such that the output tracking error performance is well obtained. Finally, a simulation example demonstrates the effectiveness and robustness of the proposed controller.