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

Abstract: 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.

Key words: multi unmanned aerial vehicles(UAVs), formation control, formation reconfiguration, diversity particle swarm optimization(PSO) algorithm, flight path planning, ant colony optimization(ACO) algorithm