Non-fragile H consensus of linear multi-agent systems with interval-bounded variations

Xiang Gui Guo, Jian Liang Wang, Fang Liao

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

4 Citations (Scopus)

Abstract

This paper studies the distributed non-fragile H consensus problems for linear multi-agent systems with external disturbances and unknown initial disturbances under switching weighted balanced directed topologies. The designed controllers are insensitive to multiplicative controller coefficient variations. Sufficient conditions for the existence of the proposed control strategy are also obtained by using linear matrix inequality (LMI) technique. It is worth mentioning that instead of requiring the coupling strength among neighboring agents to be larger than a threshold value as in previous literature, the coupling strength in this paper can be determined by solving some LMIs. Finally, a numerical example is presented to show the effectiveness of the proposed method.

Original languageEnglish
Title of host publication2015 23rd Mediterranean Conference on Control and Automation, MED 2015 - Conference Proceedings
EditorsVictor Munoz, Joseba Quevedo, Jorge L. Martinez, Jesus Morales
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1039-1044
Number of pages6
ISBN (Electronic)9781479999361
DOIs
Publication statusPublished - 14 Jul 2015
Externally publishedYes
Event23rd Mediterranean Conference on Control and Automation, MED 2015 - Torremolinos, Spain
Duration: 16 Jun 201519 Jun 2015

Publication series

Name2015 23rd Mediterranean Conference on Control and Automation, MED 2015 - Conference Proceedings

Conference

Conference23rd Mediterranean Conference on Control and Automation, MED 2015
Country/TerritorySpain
CityTorremolinos
Period16/06/1519/06/15

Keywords

  • Consensus control
  • Linear matrix inequality (LMI)
  • Multi-agent systems
  • Non-fragile control
  • Switching topologies

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Control and Optimization

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