电子电气工程与控制

基于自适应方法的多无人机编队队形控制

  • 张佳龙 ,
  • 闫建国 ,
  • 张普
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  • 西北工业大学 自动化学院, 西安 710129

收稿日期: 2019-08-15

  修回日期: 2019-09-04

  网络出版日期: 2019-10-24

基金资助

西北工业大学博士论文创新基金(CX201955)

Multi-UAV formation forming control based on adaptive method under wind field disturbances

  • ZHANG Jialong ,
  • YAN Jianguo ,
  • ZHANG Pu
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  • School of Automation, Northwestern Polytechnical University, Xi'an 710129, China

Received date: 2019-08-15

  Revised date: 2019-09-04

  Online published: 2019-10-24

Supported by

Innovation Foundation for Doctor Dissertation of Northwestern Polytechnical University (CX201955)

摘要

针对"长机-僚机"近距编队队形因风场扰动而不能保持期望队形的问题,首先,提出了一种自适应队形保持控制的方法,该方法可用于抵消因风场不确定性对无人机的横侧向和前行方向所产生的距离误差,同时能够保持无人机编队稳定飞行。其次,由于风场的不确定性会引起"长机-僚机"之间的动力学发生变化,因此设计了一种基于"长机-僚机"相对运动模型的自适应控制律用以估计风场在3个方向的大小,进而控制无人机之间的相对运动以消除风场不确定性所产生的距离误差并保持速度的一致性,最终实现保持期望的队形。再次,通过构建合理的李雅普诺夫函数,证明无人机编队在风场干扰下能够保持编队稳定飞行,同时"长机-僚机"之间相对横向、横侧向以及纵向的距离误差均接近零。最后,通过仿真验证:所提出的自适应控制方法具有良好的鲁棒性,这为工程实践提供理论依据。

本文引用格式

张佳龙 , 闫建国 , 张普 . 基于自适应方法的多无人机编队队形控制[J]. 航空学报, 2020 , 41(1) : 323385 -323385 . DOI: 10.7527/S1000-6893.2019.23385

Abstract

The "leader-follower" closed formation is unable to keep the desired formation due to wind disturbances. To solve this problem, an adaptive formation keeping control method is proposed to counteract the lateral and forward distance error due to the uncertain wind disturbances and to maintain the desired formation flight. Since uncertain wind disturbances change the dynamics between the leader and the follower, this paper designs an adaptive control law based on the "leader-follower" model to accurately estimate the magnitude and direction of the wind in three-dimensional space. Subsequently, it helps control the relative motion between UAVs to eliminate the distance error and keep the consensus of velocity, which can achieve the desired formation. It is proved that the "leader-follower" formation can keep flight-stability in windy field environment, and the relative lateral, forward, and longitudinal distance errors between them are close to zero according to a reasonable Lyapunov function. The simulation results show that the proposed adaptive control method has good robustness, providing a theoretical basis for engineering practice.

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