Recovery trajectory optimization for UAV towed aerial recovery based on trajectory mapping

被引：0
|
作者：
Wang H. [1 ,2 ]
Wang Y. [1 ,2 ,3 ]
Liu Y. [1 ,2 ,4 ]
机构：
[1] School of Automation Science and Electrical Engineering, Beihang University, Beijing
[2] The Science and Technology on Aircraft Control Laboratory, Beihang University, Beijing
[3] Shenyuan Honors College, Beihang University, Beijing
[4] Beijing Institute of Astronautical Systems Engineering, Beijing
来源：
Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica | 2023年 / 44卷 / 20期
基金：
中国国家自然科学基金;
关键词：
aerial recovery; Bidirectional Long Short-Term Memory (BiLSTM); cable-drogue-UAV assembly; neural network; trajectory mapping; trajectory optimization;
D O I：
10.7527/S1000-6893.2023.28775
中图分类号：
学科分类号：
摘要：
For the problem of trajectory optimization in the process of Unmanned Aerial Vehicle（UAV）towed aerial recovery，an optimization method of UAV recovery trajectory is proposed based on trajectory mapping. First，an aerial recovery system model，including the cable-drogue-UAV assembly model and the wing fold model，is established. Second，the idea of trajectory mapping is put forward，and the accurate mapping relationship between the recovery instruction and the recovery trajectory in the recovery system is established by using the Bidirectional Long Short-Term Memory（BiLSTM）neural network. Third，the trajectory mapping network is utilized to predict the real recovery trajectory under different instructions in real time，and the Particle Swarm Optimization（PSO）algorithm is used to optimize the optimal recovery instruction according to the calculated predicted trajectory cost. Finally，the simulation results show that the proposed trajectory mapping network has high prediction accuracy and calculation speed，and the proposed optimization method can achieve stable and rapid recovery of UAV. © 2023 AAAS Press of Chinese Society of Aeronautics and Astronautics. All rights reserved.
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