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

Shen Yan, Zhou Gu, Ju H. Park, Mouquan Shen

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

This paper investigates the fusion-based event- triggered H∞ state estimation of autonomous surface vehi- cles (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∞ state estimation error system with network-induced delays. Then, sufficient conditions are deduced for solving H∞ estimator gain and triggering matrix of FETM. Lastly, some simulation results are given to illustrate the merits of the theoretical method.

Original languageEnglish
Pages (from-to)7541-7551
Number of pages11
JournalIEEE Transactions on Intelligent Transportation Systems
Volume25
Issue number7
DOIs
StatePublished - 2024

Keywords

  • Fusion-based event-triggered mechanism
  • Ha state estimation
  • autonomous surface vehicles
  • cyber-attacks
  • measurement outliers
  • networked systems

Fingerprint

Dive into the research topics of 'Fusion-Based Event-Triggered H State Estimation of Networked Autonomous Surface Vehicles With Measurement Outliers and Cyber-Attacks'. Together they form a unique fingerprint.

Cite this