Distributed formation control of multiple flight vehicles with considering communication delay

Li Wei*, Wen Qiuqiu, Jiang Huan, Xia Qunli

*Corresponding author for this work

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

Abstract

The distributed formation control of multiple flight vehicles is researched based on the reentry scenario in this paper. The leader information and neighboring follower information are transmitted to each follower in the formation system, and then the weighted adjacency matrix is chosen and the distributed sliding mode control algorithm in the line-of-sight (LOS) is designed for the accurately linearized double-integrator system to suppress the adverse effects of the communication delay and the external disturbance. The finite-time convergence of the formation tracking errors is rigorously proved. The expected position vector of each follower is given and numerical simulations are conducted subsequently to verify the effectiveness of the proposed control algorithm. The presented results can be applied to deal with the consensus tracking problem for the cluster system with one leader.

Original languageEnglish
Title of host publication2021 12th International Conference on Mechanical and Aerospace Engineering, ICMAE 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages394-406
Number of pages13
ISBN (Electronic)9781665433211
DOIs
Publication statusPublished - 16 Jul 2021
Event12th International Conference on Mechanical and Aerospace Engineering, ICMAE 2021 - Virtual, Athens, Greece
Duration: 16 Jul 202119 Jul 2021

Publication series

Name2021 12th International Conference on Mechanical and Aerospace Engineering, ICMAE 2021

Conference

Conference12th International Conference on Mechanical and Aerospace Engineering, ICMAE 2021
Country/TerritoryGreece
CityVirtual, Athens
Period16/07/2119/07/21

Keywords

  • Communication delay
  • Distributed formation control
  • Finite-time convergence
  • Multiple flight vehicles
  • Reentry scenario

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