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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。
In view of the various threats in the enemy defensive area, in order to realize the concealed penetration prevention and implement the effective attack on the enemy, many UAV formations need to be reconstructed and controlled in the course of penetration, and the mutual avoidance problems in formation Communication constraints also need to be considered. By constructing a drone virtual pilot formation model and introducing a neighbor set, the distributed model predictive control (DMPC) is used to construct the reconstructed cost function of multi-UAV formation simultaneously. The improved quantum particle swarm optimization (RQPSO) algorithm is proposed to solve the problem. The results are compared with the results of particle swarm optimization. The simulation results show that the proposed algorithm can effectively control the formation of multi-UAV formation autonomously reconfiguration and realize the task of concealed and hidden security.