Robust formation control of unmanned aerial vehicle swarms subject to jointly connected directed switching topologies

被引:0
|
作者
Kang Y. [1 ,2 ]
Mao K. [2 ]
Cheng J. [1 ]
Luo D. [3 ]
Liu W. [2 ]
Wang S. [4 ,5 ]
机构
[1] Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen
[2] Aviation Foundation College, Naval Aviation University, Yantai
[3] School of Aeronautics and Astronautics, Xiamen University, Xiamen
[4] College of Artificial Intelligence, Yantai Institute of Technology, Yantai
[5] Department of Computer Science and Technology (DCST), Tsinghua University, Beijing
关键词
jointly connected; robust control; time-varying formation; trajectory tracking; unmanned aerial vehicle swarm;
D O I
10.1360/SST-2022-0026
中图分类号
学科分类号
摘要
The problem of robust time-varying formation (TVF) and trajectory tracking control for unmanned aerial vehicle (UAV) swarms with external disturbances under jointly connected directed switching topologies was investigated. First, a distributed formation control approach of UAV swarms was designed based on the error in the actual flight state information, expected flight state information, and trajectory information of UAVs that must be tracked, as well as the error information between the expected flight state and actual flight state of UAVs that can communicate with other UAVs under jointly connected directed switching topologies. Afterwards, the TVF and trajectory tracking problem of the swarm system was converted into an asymptotic state control problem using a special type of variable replacement. Furthermore, a sufficient condition for the asymptotic state of the system is proposed and proven using an established piecewise continuous Lyapunov functional. Finally, the simulation results confirmed that the proposed approach can actualize the TVF and trajectory tracking flight control of UAV swarms. © 2023 Chinese Academy of Sciences. All rights reserved.
引用
收藏
页码:2115 / 2126
页数:11
相关论文
共 39 条
  • [1] Duan H B, Shen Y K, Zhao Y J, Et al., Review of technological hotspots of unmanned aerial vehicle in 2020 (in Chinese), Sci Technol Rev, 39, pp. 233-247, (2021)
  • [2] Wang Y, Wang D B, Wang J H., A convex optimization based method for multiple UAV autonomous formation reconfiguration (in Chinese), Sci Sin Tech, 47, pp. 249-258, (2017)
  • [3] Zong Q, Zhang R L, Dong Q, Et al., Adaptive sliding mode control for fixed-wing unmanned aerial vehicle (in Chinese), J Harbin Inst Technol, 50, pp. 147-155, (2018)
  • [4] Zhao J X, Duan H B, Zhao Y J, Et al., Consensus control of manned-unmanned aerial vehicle swarm based on hierarchy interaction of pigeons, J Shanghai Jiaotong Univ, 54, pp. 973-981, (2020)
  • [5] Wei R X, Zhang Q R, Xu Z F, Et al., A brain-like mechanism for developmental UAV’s collision avoidance (in Chinese), Contl Theor Appl, 36, pp. 175-182, (2019)
  • [6] Guo L, Yu X, Zhang X, Et al., Safety control system technologies for UAVs: Review and prospect, Sci Sin-Inf, 50, pp. 184-194, (2020)
  • [7] Niu Y F, Zhu Y T, Li H N, Et al., Small sample vehicle target recognition using component model for unmanned aerial vehicle (in Chinese), J. Natl Univ Def Technol, 43, pp. 117-126, (2021)
  • [8] Zhang H, Xin B, Dou L, Et al., A review of cooperative path planning of an unmanned aerial vehicle group, Front Inform Technol Electron Eng, 21, pp. 1671-1694, (2020)
  • [9] Wang J, Zhou Z, Wang C, Et al., Multiple quadrotors formation flying control design and experimental verification, Unman Syst, pp. 47-54, (2019)
  • [10] Xu Y, Luo D L, Zhou L P, Et al., A gain matrix approach for robust distributed 3D formation control with second order swarm systems (in Chinese), Sci Sin Tech, 50, pp. 461-474, (2020)