Disturbance‐observer‐based adaptive neural control for switched nonlinear systems with average dwell time

Abstract

AbstractIn this article, a robust control framework is developed for nonstrict‐feedback switched nonlinear systems in the presence of unknown time‐varying delays and external disturbances. Taking into account the differences in the disturbance of each subsystem, a novel disturbance observer (DO) based on the auxiliary system is proposed for the first time. The auxiliary system is designed with the same order as that of the studied switched system, whose state variables are used to adjust the parameters of the DO in real time. Furthermore, by improving the stability condition in the frame of average dwell time (ADT), a robust control law design method based on the DO is extended to the switched system. Based on the Lyapunov–Krasovskii function, an improved delay processing method is developed, which can eliminate the widely used growth assumptions of unknown functions. Based on the DO and neural network, a robust adaptive neural network controller is constructed, and the ADT approach is adopted to analyze the semiglobal uniform ultimate boundedness of all closed‐loop system signals. Finally, the effectiveness of the proposed control scheme is further verified through simulation studies of an electromechanical system.