Systems Engineering and Electronics ›› 2022, Vol. 44 ›› Issue (9): 2840-2848.doi: 10.12305/j.issn.1001-506X.2022.09.18

• Systems Engineering • Previous Articles     Next Articles

UAV formation rapid assembly method based on improved Quatre algorithm

Tianye SUN1, Wei SUN1,*, Jianjun WU2   

  1. 1. School of Aerospace Science and Technology, Xidian University, Xi'an 710071, China
    2. The 365th Research Institute, Northwestern Polytechnical University, Xi'an 710129, China
  • Received:2021-07-21 Online:2022-09-01 Published:2022-09-09
  • Contact: Wei SUN

Abstract:

To improve the stability of multiple unmanned aerial vehicle (UAV) in the process of formation assembly, this paper proposes a UAV formation method based on improved quasi-affine transformation evolutionary (IQuatre) algorithm. First of all, based on distributed model predictive control (DMPC), a motion prediction model of the UAV formation is established. By predicting the "future state" of the UAV, the risk of collision within the formation is avoided. The mathematical model of rolling optimization improves the stability of the UAV to reach the designated position. UAV is better and faster to join the formation flight. Secondly, the Quatre algorithm is improved on population optimization by the parent individuals carrying the best genes selectively added to the offspring population to speed up population convergence. The experimental results show that the UAV formation based on the DMPC has no UAV collision, and reduces the position deviation during the UAV adjustment state. Comparing simulations verify that the IQuatre algorithm can improve the stability of the formation assembly. Compared with the original Quatre algorithm, the average number of iterations is reduced by 5.2%, the calculation time is saved by 4.6%, and the position error is reduced by 0.45 m.

Key words: unmanned aerial vehicle (UAV) formation, distributed model predictive control (DMPC), improved quasi-affine transformation evolutionary (IQuatre), rolling optimization, population optimization

CLC Number: 

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