Event-Triggered State Estimation for Networked Switched Systems: An Output Predictor Approach

Abstract

In this article, we investigate the event-triggered state estimation for networked switched systems with (a)synchronous switching. A new multimode output predictor-based sampled-data observer and an event-triggered mechanism are proposed. Between event-triggered sampling times, an output predictor is utilized to compensate for the impact of sampling, and at the sampling instants, the predicted output is reset with the updated sampled output. Two scenarios are considered: the observer's switching signal is synchronous with the system's switching signal, and the switching signals among them are asynchronous, and frequent switching is allowed during interevent intervals. Average dwell time and linear matrix inequalities techniques are employed to guarantee the global uniform exponential convergence of the proposed observer. Moreover, Zeno phenomenon can be ruled out by proving the existence of a positive lower bound of interevent intervals. Finally, the effectiveness of the proposed approach is illustrated by a circuit system and an academic example.