Distributed Indegree-weighted Kalman Consensus Filter Algorithm Against Packet-dropping

Chen Xia, Hao Yang, Tiancheng Li

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

Abstract

In this paper, on the basis of the Kalman consensus filter (KCF), the indegree-weighted Kalman consensus filter (IKCF) is proposed for the distributed network in the presence of packet-dropping. In the IKCF, the extended sensor measurement model is introduced to ensure all sensors can achieve measurements under packet-dropping. Further, we designed the quantization function based on the indegree to combat the transmission error. Experimental results illustrate the superior performance of the proposed IKCF.

Original languageEnglish
Title of host publicationProceedings - 12th IEEE International Conference on Control, Automation and Information Sciences, ICCAIS 2023
EditorsTruong Xuan Tung, Tran Cong Tan, Cao Huu Tinh
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages535-540
Number of pages6
ISBN (Electronic)9798350328783
DOIs
StatePublished - 2023
Event12th IEEE International Conference on Control, Automation and Information Sciences, ICCAIS 2023 - Hanoi, Viet Nam
Duration: 27 Nov 202329 Nov 2023

Publication series

NameProceedings - 12th IEEE International Conference on Control, Automation and Information Sciences, ICCAIS 2023

Conference

Conference12th IEEE International Conference on Control, Automation and Information Sciences, ICCAIS 2023
Country/TerritoryViet Nam
CityHanoi
Period27/11/2329/11/23

Keywords

  • extended sensor measurement model
  • IKCF
  • packet-dropping
  • quantization function.

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