多无人机多任务对地攻击协同任务分配

针对多无人机对地协同攻击多任务分配问题,通过合理假设对问题进行抽象简化的基础上,建立了基于任务分配收益和代价的总体分配效能函数模型,并以此模型作为任务分配方案的评估标准。引入各种操作符重新定义了离散粒子群优化算法的速度以及位置更新公式,建立了算法实现的基本流程,并利用该DPSO优化算法对任务分配模型进行求解。分别针对多UAV单任务,单UAV多任务以及多UAV多任务进行仿真分析,结果表明,DPSO算法比遗传算法具有更好的全局搜索能力和收敛速度,通过仿真验证了任务分配模型的合理性和正确性,验证了算法的有效性和相对于遗传算法的优越性。

Multi-UAV Cooperative Task Allocation of Multi-task Air-to-ground Attack

According to multi-task allocation problem of multi-shipboard UAV cooperative attack,function model of the overall allocation performance is established based on task allocation of benefits and costs through reasonable assumptions to abstract and simplify the problem,and this model is selected as a evaluation criteria of task allocation scheme. The speed of the DPSO algorithm and the position update formula are redefined by introduction of various operators,the basic steps of DPSO algorithm and implementation process are established. And the DPSO optimization algorithm is used for the solution to task allocation model. The conditions of multi-UAV single task,single UAV multi-task and multi-UAV multi-task are simulated and analyzed. The results show that the DPSO algorithm has better global searching ability and convergence speed than that of genetic algorithm,the rationality and correctness of the task allocation model are verified through simulation,as well as the effectiveness of the algorithm and the superiority relative to genetic algorithm are verified.