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Fuzzy-based filtering of autonomous vehicle system via memory-based event-triggered mechanism

  • Yaxin Gu*
  • , Weiyi Zhao
  • , Xinxin Liu
  • , Xiaojie Su
  • , Jianxing Liu
  • *Corresponding author for this work
  • Nanjing University of Information Science & Technology
  • Chongqing University

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

Abstract

The fuzzy reduced-based filtering problem within autonomous vehicles featuring dynamic positioning systems is employed via an enhanced event-triggered scheme. A reduced-based filtering approach is proposed capable of approximating the original high-order model with a given system performance level. The stability analysis is solved by employing the memorybased event-triggered scheme. Thus the usage of network transmission computational resources is saved effectively.

Original languageEnglish
Title of host publicationProceedings of the 3rd Conference on Fully Actuated System Theory and Applications, FASTA 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages325-330
Number of pages6
ISBN (Electronic)9798350373691
DOIs
StatePublished - 2024
Event3rd Conference on Fully Actuated System Theory and Applications, FASTA 2024 - Shenzhen, China
Duration: 10 May 202412 May 2024

Publication series

NameProceedings of the 3rd Conference on Fully Actuated System Theory and Applications, FASTA 2024

Conference

Conference3rd Conference on Fully Actuated System Theory and Applications, FASTA 2024
Country/TerritoryChina
CityShenzhen
Period10/05/2412/05/24

Keywords

  • Autonomous vehicles
  • filtering
  • fuzzy model
  • memory-based event-triggered mechanism

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