Integrated Design of Fully Distributed Adaptive State Estimation and Consensus Control for Multi-agent Systems

Jiazhu Huang, Yan Li, Yuezu Lv*

*Corresponding author for this work

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

3 Citations (Scopus)

Abstract

In this paper, the problem of fully distributed adaptive state estimation and consensus control for linear multi-agent systems is investigated. By designing fully distributed adaptive output tracking observers, the entire output information is available to each agent, and local state estimators based on the estimated output is constructed to estimate the overall state of multi-agent systems. The consensus control protocol based on state estimation for multi-agent systems is designed to ensure the agents achieve consensus. The proposed control input of each agent relies on its own estimation of the entire state. Theoretical analysis proves the effectiveness of the algorithm and practical applications are given by simulation.

Original languageEnglish
Title of host publicationNeural Information Processing - 30th International Conference, ICONIP 2023, Proceedings
EditorsBiao Luo, Long Cheng, Zheng-Guang Wu, Hongyi Li, Chaojie Li
PublisherSpringer Science and Business Media Deutschland GmbH
Pages226-237
Number of pages12
ISBN (Print)9789819980789
DOIs
Publication statusPublished - 2024
Event30th International Conference on Neural Information Processing, ICONIP 2023 - Changsha, China
Duration: 20 Nov 202323 Nov 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14447 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference30th International Conference on Neural Information Processing, ICONIP 2023
Country/TerritoryChina
CityChangsha
Period20/11/2323/11/23

Keywords

  • Adaptive output tracking
  • Consensus control
  • Distributed state estimation
  • Multi-agent systems

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