Time-variant consensus tracking control for networked planar multi-agent systems with non-holonomic constraints

Jun Zhao*, G-P Liu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

37 Downloads (Pure)

Abstract

A time-variant consensus tracking control problem for networked planar multi-agent systems with non-holonomic constraints is investigated in this paper. In the time-variant consensus tracking problem, a leader agent is expected to track a desired reference input, simultaneously, follower agents are expected to maintain a time-variant formation. To solve the time-variant consensus tracking problem of planar multi-agent systems with non-holonomic constraints, a time-variant consensus tracking control strategy is designed on the basis of an unidirectional topology structure. One of main contributions of this paper is the time-variant consensus tracking protocol for general time-variant formations of planar multi-agent systems with non-holonomic constraints, the other main contribution of this paper is an active predictive control strategy, where predictions of agents are generated actively, so that the computational efficiency is improved than passive approaches. The proposed control strategy is verified by two types of time-varying formations of wheeled mobile robots, and the experimental results show that the proposed control strategy is effective for general time-variant consensus tracking problems of planar multi-agent systems with non-holonomic constraints in local and worldwide networked environments.

Original languageEnglish
Pages (from-to)1-23
Number of pages23
JournalJournal of Systems Science and Complexity
DOIs
Publication statusAccepted/In press - 24 Jun 2017

Keywords

  • Consensus tracking
  • networked multi-agent system
  • networked predictive control
  • nonholonomic constraint
  • time-variant consensus

Fingerprint

Dive into the research topics of 'Time-variant consensus tracking control for networked planar multi-agent systems with non-holonomic constraints'. Together they form a unique fingerprint.

Cite this