Barrier Function Based Consensus of High-Order Nonlinear Multi-agent Systems with State Constraints

Junjie Fu*, Guanghui Wen, Yuezu Lv, Tingwen Huang

*Corresponding author for this work

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

3 Citations (Scopus)

Abstract

Consensus control of a class of high-order nonlinear multi-agent systems subject to multiple state constraints and input saturation is studied in this work. Barrier functions are employed to design a distributed controller which achieves consensus without violating the state constraints and input saturation provided that some feasibility conditions on the initial states and controller parameters are satisfied. The feasibility conditions can be checked off-line. Backstepping method and Lyapunov analysis are employed to study the convergence properties of the designed controller.

Original languageEnglish
Title of host publicationNeural Information Processing - 26th International Conference, ICONIP 2019, Proceedings
EditorsTom Gedeon, Kok Wai Wong, Minho Lee
PublisherSpringer
Pages492-503
Number of pages12
ISBN (Print)9783030367107
DOIs
Publication statusPublished - 2019
Externally publishedYes
Event26th International Conference on Neural Information Processing, ICONIP 2019 - Sydney, Australia
Duration: 12 Dec 201915 Dec 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11954 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference26th International Conference on Neural Information Processing, ICONIP 2019
Country/TerritoryAustralia
CitySydney
Period12/12/1915/12/19

Keywords

  • Barrier function
  • Consensus
  • Input saturation
  • Multi-agent system
  • Nonlinear systems
  • State constraints

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