Robust Adaptive Control of nonlinear switched Systems under external disturbances

In this work, a robust adaptive neural network control is proposed for a class of nonlinear switched systems with external disturbances. The main idea is a design based on the approximation description of neural networks and the dwell-time approach. Under the separation of disturbances, we establish new linear matrix inequalities to give the control law. Stability analysis shows that all the closed-loop system signals are uniformly ultimately bounded, and the steady-state tracking error can be made arbitrarily small by appropriately choosing control parameters. The simulation results demonstrate the effectiveness of the proposed controllers.