Fusion-Based Event-Triggered H∞ State Estimation of Networked Autonomous Surface Vehicles With Measurement Outliers and Cyber-Attacks

This paper investigates the fusion-based event-triggered
$H_{\infty} $
state estimation of autonomous surface vehicles (ASVs) against measurement outliers and cyber-attacks. To release communication burden, a novel fusion-based event-triggered mechanism (FETM) dependent on the fusion of historical system outputs is proposed. There exist two advantages of this mechanism: 1) the use of fusion signal is able to avoid the information loss between two sampling instants and reduce the redundant triggering events resulted from system disturbances and noises; 2) by requiring the error signal in the triggering condition not only lager than a lower threshold but also less than an upper threshold, the false triggering events incurred by measurement outliers also can be discarded. Then, a time-varying delay system is established to represent the event-triggered
$H_{\infty} $
state estimation error system with network-induced delays. Then, sufficient conditions are deduced for solving
$H_{\infty }$
estimator gain and triggering matrix of FETM. Lastly, some simulation results are given to illustrate the merits of the theoretical method.