基于粒子群算法的多无人机任务分配方法  

Method of tasks allocation of multi-UAVs based on particles swarm optimization

作　　者：李炜[1] 张伟[1] 

机构地区：[1]电子科技大学电子科学技术研究院,成都610054

出　　处：《控制与决策》2010年第9期1359-1363,1368,共6页Control and Decision

基　　金：国防预研项目(402030203);电子科技大学中青年学术带头人培养计划项目

摘　　要：作为多无人机系统应用的一项关键技术,任务分配是一个多维互异离散变量的优化问题.采用混合整数线性规划方法构造优化函数,并利用群智算法中的粒子群算法来求最优解,这样可以解决多无人机的任务分配问题.针对互异性要求进行必要的算法改进.数值仿真实验表明,该粒子群算法可以迅速找到优化函数的最优解,从而高效地实现多无人机的任务分配.Task allocation is a kind of key technology in the application of multi-UAVs systems, and it is a mutually exclusive multi-dimensions optimal problem. Mixed integer linear program is applied to build the optimal function, and particle swarm optimization（PSO） algorithm is utilized for searching the best solution in order to realize the task allocation of multi-UAVs system. In the PSO algorithm, it is necessary to make some modification to suit for the acquirement of mutually exclusive. The numerical simulation shows that the presented algorithm can find the optimal solution rapidly and accomplish the task allocation of multi-UAVs efficiently.

关 键 词：多无人机 任务分配 粒子群算法 多维互异变量 代价函数 

分 类 号：V249.122[航空宇航科学与技术—飞行器设计]