Skip to main navigation Skip to search Skip to main content

Weighted consensus for multiple Lagrangian systems under a directed graph

  • Jie Mei*
  • *Corresponding author for this work
  • Harbin Institute of Technology Shenzhen

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

Abstract

In this paper, we study the leaderless consensus problem for multiple Lagrange systems in the presence of parametric uncertainties under a directed graph. By introducing an integrate term in the auxiliary variable design, the final consensus equilibrium can be explicitly derived. We show that this equilibrium is dependent on three factors, namely, the interactive topology, the initial positions of the agents, and the control gains of the proposed control algorithm. For the case where the graph associated with the interactive topology is strongly connected, a Lyapunov based method is presented to show the consensus convergence, where the input-To-state stability is repeatedly used. We also give discussions on the consensus convergence when the graph contains a directed spanning tree. The leader-follower tracking problem and average consensus problem are also presented under special conditions.

Original languageEnglish
Title of host publicationProceedings - 2015 Chinese Automation Congress, CAC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1064-1068
Number of pages5
ISBN (Electronic)9781467371896
DOIs
StatePublished - 13 Jan 2016
Externally publishedYes
EventChinese Automation Congress, CAC 2015 - Wuhan, China
Duration: 27 Nov 201529 Nov 2015

Publication series

NameProceedings - 2015 Chinese Automation Congress, CAC 2015

Conference

ConferenceChinese Automation Congress, CAC 2015
Country/TerritoryChina
CityWuhan
Period27/11/1529/11/15

Keywords

  • Lagrange system
  • Multi-Agent systems
  • consensus
  • cooperative control
  • directed graph

Fingerprint

Dive into the research topics of 'Weighted consensus for multiple Lagrangian systems under a directed graph'. Together they form a unique fingerprint.

Cite this