多无人机编队协同控制软件平台设计与仿真  

Design and Simulation of Multi-UAVs Coordinated Formation Control Software Platform

作　　者：李春 宋晓程 李芳芳[1] LI Chun;SONG Xiao-cheng;LI Fang-fang(Beijing Institute of Electronic System Engineering,Beijing 100854,China)

机构地区：[1]北京电子工程总体研究所,北京100854

出　　处：《现代防御技术》2018年第6期143-150,共8页Modern Defence Technology

摘　　要：在战场环境瞬息万变、作战任务日益复杂的现代战争中,多架无人机编队协同完成复杂的作战任务已成为一种趋势。多无人机编队控制及重构是多无人机系统的核心内容和关键技术。基于微粒群算法、蚁群算法研究了多无人机编队控制及重构、航线规划及重规划问题,特别是在解决编队重构问题时,提出一种多样性微粒群算法。设计了多无人机编队飞行协同控制平台,仿真结果表明,标准微粒群算法、蚁群算法等智能算法可以较好解决编队控制、编队重构和航线规划问题,多样性微粒群算法具有更强的全局寻优能力。In the modern warfare with increasingly complex operational tasks and changing battlefield environment,it has become a trend for multi unmanned aerial vehicles( UAVs) to cooperate to complete complex operational tasks. The key technology of multi-UAVs system involves multi-UAVs formation flight control and reconfiguration. We researched the problem of multi-UAVs formation control,reconfiguration,as well as path planning using particle swarm optimization( PSO) and ant colony optimization( ACO) algorithm. For the formation reconfiguration,we considered the reconfiguration in a dynamical environment and gave a method based on a diversity PSO algorithm. We also developed a multi-UAVs coordinated formation flight control platform. The simulation results showed that the intelligent algorithms such as PSO and ACO can solve formation control,formation reconfiguration and flight path planning problem well,and the diversity PSO algorithm has stronger global optimization ability.

关 键 词：多无人机 编队控制 编队重构 多样性微粒群算法 航线规划 蚁群算法 

分 类 号：V279[航空宇航科学与技术—飞行器设计] V323.18