Event-triggered secure state estimation under sparse sensor attacks

Abstract

This paper is concerned with the secure state estimation problem for a class of cyber-physical systems (CPSs) with multiple sensors equipped with a decentralized event-triggering (ET) mechanism. Compared with the traditional secure state estimators, the introduction of ET mechanism mitigates the unnecessary data transmission and brings more useful information for secure state estimation. To make full use of the introduced event-triggering conditions which are not corrupted by the adversary, a novel data consolidation algorithm is proposed to consolidate the collected information. Then, a necessary and sufficient condition for the robust observability of the CPSs equipped with ET mechanism under sparse sensor attacks is provided, and a switched gradient descent algorithm is proposed to estimate the system state from the consolidated data. It is shown that through consolidating the collected information, introducing ET mechanism helps improve the resilience against sparse sensor attacks. Finally, a numerical simulation is provided to illustrate the effectiveness of the proposed algorithms.