Multirobot System Formation Control With Multiple Performance and Feasibility Constraints

Xu Jin, Shi Lu Dai, Jianjun Liang, Dejun Guo

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


In this work, we propose a novel framework to address the formation control problem for a class of multirobot systems with two types of constraints, namely the performance constraints and the feasibility constraints. For the performance constraints, we consider the constraint requirements on the distance tracking errors between the real and the desired trajectories for each robot, so that to ensure precise tracking of the robot without deviating too much from its desired trajectory, as well as the constraints on the interrobot distance, so that to ensure the safe operation of the team. For the feasibility constraints, we consider the constraints on the heading angle, so that the controllers designed in the brief are feasible. Universal barrier functions are adopted in the controller design and analysis, which is a generic framework that can address systems with different types of constraints in a unified controller architecture. Through rigorous analysis, exponential convergence rate can be guaranteed on the distance tracking errors, while all constraints are satisfied during the operation. A simulation example and an experiment using three AmigoBot mobile robots further demonstrate the efficacy of the proposed control framework.

Original languageEnglish
Pages (from-to)1766-1773
Number of pages8
JournalIEEE Transactions on Control Systems Technology
Issue number4
StatePublished - Jul 1 2022

Bibliographical note

Publisher Copyright:
© 1993-2012 IEEE.


  • Adaptive control
  • feasibility constraints
  • formation control
  • multirobot systems
  • performance constraints
  • universal barrier functions

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering


Dive into the research topics of 'Multirobot System Formation Control With Multiple Performance and Feasibility Constraints'. Together they form a unique fingerprint.

Cite this