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引用本文:伍友利,叶圣涛,方洋旺,朱圣怡,张丹旭.固定翼无人机群的集群和避障控制[J].国防科技大学学报,2019,41(5):103-110.[点击复制]
WU Youli,YE Shengtao,FANG Yangwang,ZHU Shengyi,ZHANG Danxu.Flocking and obstacles avoidance for fixed-wing unmanned aerial vehicle swarm[J].Journal of National University of Defense Technology,2019,41(5):103-110[点击复制]
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固定翼无人机群的集群和避障控制
伍友利1, 叶圣涛1, 方洋旺1,2, 朱圣怡1, 张丹旭1
(1.空军工程大学 航空工程学院, 陕西 西安 710038;2.西北工业大学 无人系统研究院, 陕西 西安 710072)
摘要:
    针对传统的集群控制算法需要获取通信范围内相邻质点的位置和速度信息才能够计算控制量的问题,提出一种新的无须获得相邻无人机速度的六自由度固定翼无人机群的集群和避障控制方法。将通信范围内的无人机均视为障碍物,采用统一的计算方法获得控制量,并且证明了算法的稳定性。通过建立六自由度无人机线性化控制模型,将改进的质点集群算法应用于无人机群控制系统中,将无人机控制设计成六自由度无人机的跟踪回路和质点无人机的导引回路,并证明通过选取合适的跟踪回路控制参数,确保整个无人机集群控制是稳定的。通过六自由度无人机编队仿真验证了所提算法的有效性。
关键词:  固定翼  无人机群  六自由度  集群  避障
DOI:10.11887/j.cn.201905015
投稿日期:2018-06-20  
基金项目:2017全国博士后创新人才支持计划资助项目(BX201700104)
Flocking and obstacles avoidance for fixed-wing unmanned aerial vehicle swarm
WU Youli1, YE Shengtao1, FANG Yangwang1,2, ZHU Shengyi1, ZHANG Danxu1
(1.Aeronautics and Astronautics Engineering College, Air Force Engineering University, Xi′an 710038, China;2.Unmanned System Research Institute, Northwestern Polytechnical University, Xi′an 710072, China)
Abstract:
    In order to calculate control volume, the traditional flocking control algorithm is necessary to obtain the position and velocity information of adjacent particles within the communication range, a novel flocking algorithm without the velocity information of the adjacent agent for UAV (unmanned aerial vehicle) was proposed. Firstly, all UAVs within the communication range were regarded as obstacles and the control quantity was obtained by the unified calculation method. Some related theories were proved based on Lyapunov stability. Afterwards, the improved flocking algorithm was applied to UAV swarm control by establishing a six-degree-of-freedom UAV linearization control model and the whole UAV swarm consisting of the tracking loop and guidance loop is stable through selecting appropriate control parameters. Finally, the effectiveness of the proposed algorithm is verified by the numerical simulations.
Key words:  fixed-wing  unmanned aerial vehicle swarm  six-degree-of-freedom  flocking  obstacle avoidance
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