Leader-following consensus of linear multi-agent systems with strict negative imaginary uncertainties

Kai Yan*, Zhuoyue Song

*Corresponding author for this work

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

Abstract

This paper considers the leader-following consensus problem of linear multi-agent systems with strict negative imaginary (SNI) uncertainties. It is assumed that the followers have homogeneous nominal dynamics while subject to different model uncertainties with SNI property, leading to weakly heterogeneous multi-agent systems. In the case of undirected topology, the control protocol is designed for multi-agent systems based on the relative states of neighbouring followers and the leader. It is shown that the control protocol can achieve leader-following state consensus for networked systems that followers have SNI uncertainties. A necessary and sufficient condition for the nominal networked system to be negative imaginary (NI) and satisfying gain condition is presented by decoupling the feedback controller from communication topology. Furthermore, a sufficient condition in terms of linear matrix inequalities (LMI) is derived for the leader-following consensus controller. Simulation example is provided to validate the effectiveness of the results.

Original languageEnglish
Title of host publicationProceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages84-89
Number of pages6
ISBN (Electronic)9781665440899
DOIs
Publication statusPublished - 2021
Event33rd Chinese Control and Decision Conference, CCDC 2021 - Kunming, China
Duration: 22 May 202124 May 2021

Publication series

NameProceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021

Conference

Conference33rd Chinese Control and Decision Conference, CCDC 2021
Country/TerritoryChina
CityKunming
Period22/05/2124/05/21

Keywords

  • Leader-following consensus
  • Multi-agent systems
  • Negative imaginary systems
  • Robust control

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