%0 Journal Article
%T 基于RQPSO-DMPC的多无人机编队自主重构控制方法<br>Autonomous reconfiguration control method for multi-UAV formation based on RQPSO-DMPC
%A 周绍磊
%A 康宇航
%A 史贤俊
%A 戴邵武
%A 周超
%J 北京航空航天大学学报
%D 2017
%R 10.13700/j.bh.1001-5965.2016.0777
%X 摘要 针对敌方防御区域内各种威胁，为了实现隐蔽突防并实施对敌有效打击，在突防过程中多无人机（UAV）编队需要进行重构控制，并且编队内的相互避碰问题与通信约束问题也需考虑。通过建立无人机虚拟领航编队模型并引入邻居集，采用分布式模型预测控制（DMPC）同时构建多无人机编队的重构代价函数，提出采用改进量子粒子群优化（RQPSO）算法进行求解，并将求解结果与采用粒子群优化算法的结果进行对比。仿真结果表明，本文算法能够有效控制多无人机编队完成自主重构，实现安全隐蔽突防任务。<br>Abstract：For various threats in the enemy defense area, in order to achieve covert penetration and implement effective combat against enemy, the unmanned aerial vehicle (UAV) formation needs to be reconfigured in the process of penetration, and the multi-UAV collision avoidance problem and communication constraint problem within the formation also need be considered. By establishing the virtual leader formation model and introducing the neighbor set, this paper adopts distributed model predictive control (DMPC), reconstructs the cost function of multi-UAV formation reconfiguration, and proposes that the cost function is solved by adopting the revised quantum-behaved particle swarm algorithm. The solving result is compared with the result obtained by particle swarm algorithm. Simulation result shows that this algorithm can control multi-UAV formation’ autonomous reconfiguration effectively and achieve covert penetration safely.
%K 无人机(UAV)
%K 编队重构
%K 邻居集
%K 分布式模型预测控制(DMPC)
%K 量子粒子群&lt
%K br&gt
%K unmanned aerial vehicle (UAV)
%K formation reconfiguration
%K neighbor set
%K distributed model predictive control (DMPC)
%K quantum-behaved particle swarm
%U http://bhxb.buaa.edu.cn/CN/abstract/abstract14165.shtml