Volume 50 Issue 5
May  2024
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GOU J Z,LIANG T J,TAO C G,et al. Formation control and aggregation method of UAV based on consensus theory[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(5):1646-1654 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0470
Citation: GOU J Z,LIANG T J,TAO C G,et al. Formation control and aggregation method of UAV based on consensus theory[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(5):1646-1654 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0470

Formation control and aggregation method of UAV based on consensus theory

doi: 10.13700/j.bh.1001-5965.2022.0470
Funds:  National Natural Science Foundation of China (52102453); Aeronautical Science Foundation of China (20180511001)
More Information
  • Corresponding author: E-mail:liangtj@avic.com
  • Received Date: 11 Jun 2022
  • Accepted Date: 22 Jul 2022
  • Available Online: 30 Dec 2022
  • Publish Date: 28 Dec 2022
  • According to the characteristics of unmanned aerial vehicle kinematics model and the problem of remote forming, an improved consensus-based algorithm was proposed to solve the gathering-forming strategy of unmanned aerial vehicle. The coordinate system which can describe the formation directly was established. According to the characteristics of the three degree-of-freedom kinematics model of unmanned aerial vehicle with autopilot decoupled from longitudinal and transverse directions and the constraints of unmanned aerial vehicle maneuvering performance, the consensus algorithm was improved to realize the control of unmanned aerial vehicle speed, heading and flight altitude. The formation control algorithm was proposed. In addressing the parameter tuning problem caused by the large initial spacing of unmanned aerial vehicle, a gathering process was added. The particle swarm optimization algorithm was used to optimize the gathering speed to avoid trajectory conflicts, and the proposed algorithm was used to generate trajectory of each unmanned aerial vehicle after the gathering, both of which improved the adaptability of the algorithm. The simulation results show that the proposed algorithm can make unmanned aerial vehicles form a stable formation under the condition of satisfying the maneuverability constraints. Compared with the direct forming method, the proposed strategy improves the adaptability and security of the improved consistency algorithm.

     

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