Flocking for multi-agent systems with optimally rigid topology based on information weighted Kalman consensus filter

Xiaoyuan Luo, Xiaolei Li, Shaobao Li, Zhongping Jiang, Xinping Guan

Research output: Contribution to journalArticle


This paper investigates the leader-follower flocking problem of multi-agent systems. The leader with input noise is estimated by a proposed continuous-time information weighted Kalman consensus filter (IWKCF) for agents. A novel distributed flocking algorithm based on the IWKCF is further presented to make agents achieve flocking to the leader. It is shown that the proposed flocking algorithm based on the continuous-time IWKCF is asymptotically stable. Applying the topology optimization scheme, the communication complexity of system topologies of multi-agent systems is effectively reduced. Finally, simulations are provided to demonstrate the effectiveness of the proposed results.

Original languageEnglish (US)
Pages (from-to)138-148
Number of pages11
JournalInternational Journal of Control, Automation and Systems
Issue number1
StatePublished - Feb 1 2017



  • Consensus estimation
  • flocking control
  • multi-agent systems
  • topology optimization

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications

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