引用本文:费思远,鲜斌,王岭.基于群集行为的分布式多无人机编队动态避障控制[J].控制理论与应用,2022,39(1):1~11.[点击复制]
FEI Si-yuan,XIAN Bin,WANG Ling.Distributed formation control for multiple unmanned aerial vehicles with dynamic obstacle avoidance based on the flocking behavior[J].Control Theory and Technology,2022,39(1):1~11.[点击复制]
基于群集行为的分布式多无人机编队动态避障控制
Distributed formation control for multiple unmanned aerial vehicles with dynamic obstacle avoidance based on the flocking behavior
摘要点击 3943  全文点击 1378  投稿时间:2021-01-23  修订日期:2021-12-12
查看全文  查看/发表评论  下载PDF阅读器
DOI编号  10.7641/CTA.2021.10082
  2022,39(1):1-11
中文关键词  群集行为  多无人机编队  分布式控制  避障控制  实验验证
英文关键词  flocking behavior  multiple UAVs formation  distributed control  obstacle avoidance  experimental verification
基金项目  国家重点研发计划项目(2018YFB1403900), 国家自然科学基金项目(91748121, 90916004)资助.
作者单位E-mail
费思远 天津大学  
鲜斌* 天津大学 xbin@tju.edu.cn 
王岭 天津航海仪器研究所  
中文摘要
      针对无人机编队保持和动态障碍物规避控制问题, 本文提出了一种新的基于群集行为的分布式多无人机 编队控制和避障控制算法. 首先考虑了由机间气流等因素带来的干扰, 基于吸引/排斥势场和一致性方法, 设计了分 布式无人机编队的队形保持控制算法, 对编队内无人机之间的距离进行控制. 进一步考虑外部移动障碍对无人机编 队的影响, 引入了排斥势场产生避障行为, 从而控制无人机编队规避移动障碍物. 然后, 基于Lyapunov的稳定性分析 方法, 证明了多无人机编队闭环系统的稳定性和系统状态误差的最终有界性. 最后在四旋翼无人机编队实验平台上 进行了室内飞行实验验证. 实验结果表明, 本文提出的分布式群集编队避障控制算法可以有效控制无人机编队规避 外部障碍物, 且具有规避障碍后的队形重构能力.
英文摘要
      This paper presents a new distributed formation control strategy based on the flocking behavior for formation holding and dynamic obstacle avoiding control of unmanned aerial vehicles (UAVs). Firstly, considering the disturbance caused by the airflow between the UAVs, a distributed multiple UAVs formation holding controller is developed based on the attraction/repulsion potential field and consensus method, which ensures the formation maintainance between the UAVs. Secondly, considering the effects of external moving obstacles, the repulsive potential field is introduced to generate obstacle avoidance strategy for UAVs, and control the UAVs to avoid moving obstacles. Thirdly, by using the Lyapunov based stability analysis, the ultimate boundedness of system state errors and the stability of closed-loop system are proved. Finally, the indoor real-time experimental verification are performed on the multiple quadrotor UAVs testbed. Experimental results show that the proposed distributed flocking formation obstacle avoidance control strategy can effectively avoid external moving obstacles and is able to reconstruct the UAVs formation after obstacle avoidance.