Dynamic Event-triggered Adaptive Control for Uncertain Nonlinear Switched Systems Based on MDADT Method

摘要

This article deals with the dynamic event-triggered tracking control problem for nonlinear switched systems with uncertain nonlinearities. By combining neural network control technology, mode-dependent average dwell time (MDADT) switching rule and dynamic event-triggered strategy, a valid adaptive control scheme is established, which guarantees the boundedness of all signals in the resulting closed-loop system and the tracking error eventually converges to a small neighborhood of the origin under a class of switching signals with MDADT property. Unlike the existing tracking control schemes, the proposed dynamic event-triggered strategy reduce some unnecessary transmissions from controller to actuator and thus saving network resources better. Finally, the effectiveness of the proposed control design is verified by a numerical simulation.