Stochastic Event-Triggered Filtering for Nonlinear Systems Subject to Correlated Noises

Weihao Song, Yuhua Qi, Jianan Wang*, Xiaoxu Wang, Jiayuan Shan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, the event-triggered filtering problem is investigated for the nonlinear systems subject to correlated noises. The stochastic event-triggered communication strategy is adopted herein to avert the frequent information exchange and hence mitigate the network communication burden while retaining the Gaussianity of innovation process. In order to handle the correlated characteristic of the process and the measurement noises, an alternative assumption that the two-step predicted estimate satisfies Gaussian distribution is made. In the simulation, the usefulness of the developed algorithms is illustrated by two examples.

Original languageEnglish
Title of host publicationAdvances in Guidance, Navigation and Control - Proceedings of 2020 International Conference on Guidance, Navigation and Control, ICGNC 2020
EditorsLiang Yan, Haibin Duan, Xiang Yu
PublisherSpringer Science and Business Media Deutschland GmbH
Pages4757-4768
Number of pages12
ISBN (Print)9789811581540
DOIs
Publication statusPublished - 2022
EventInternational Conference on Guidance, Navigation and Control, ICGNC 2020 - Tianjin, China
Duration: 23 Oct 202025 Oct 2020

Publication series

NameLecture Notes in Electrical Engineering
Volume644 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

ConferenceInternational Conference on Guidance, Navigation and Control, ICGNC 2020
Country/TerritoryChina
CityTianjin
Period23/10/2025/10/20

Keywords

  • Correlated noises
  • Nonlinear filtering
  • Stochastic event-triggered mechanism
  • Unscented Kalman filtering

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