基于协进化多子群蚁群算法的多无人作战飞机协同航迹规划研究  

Research on Multi-UCAV Cooperative Route Planning Based on Coevolutionary Multi-Ant-Colony Algorithm

作　　者：苏菲[1] 彭辉[1] 沈林成[1] 

机构地区：[1]国防科技大学机电工程与自动化学院,湖南长沙410073

出　　处：《兵工学报》2009年第11期1562-1568,共7页Acta Armamentarii

基　　金：国家"973"重点基础研究项目资助(6138101001);国防科技大学研究生创新资助项目(B080304)

摘　　要：协同航迹规划是有效提高多无人作战飞机(UCAV)协同作战效能的关键技术之一。分析了多UCAV协同航迹规划问题中的空间协同约束、时序约束以及任务时间约束,建立了基于"协同系数"的协同航迹性能评价指标;在此基础上,通过引入蚂蚁子群间的协同进化策略,并对蚁群算法状态转移规则、信息素更新机制进行了改进,设计并实现了基于协进化多子群蚁群算法的协同航迹规划算法。仿真实验结果表明:本文方法能够很好地处理多UCAV协同任务中的各类约束条件,是一种有效的协同航迹规划方法。Cooperative route planning is one of the key technologies increasing the efficiency of multi unmanned combat aerial vehicles （UCAV） to perform cooperative missions. The space, precedence and time window constraints in multi-UCAV cooperative route planning were analyzed, and the criteria of cooperative route estimation based on cooperative coefficient were presented; The cooperative route planning algorithm based on the coevolutionary multi-ant-colony algorithm was designed and implemented by the coevolutionary strategy among multi-ant-colony and the improved state transition rule and pheromone updating mechanism. The simulated results show that the proposed method can solve the cooperative constraints efficiently, and is effective for the multi-UCAV cooperative route planning problem.

关 键 词：运筹学 无人作战飞机 协进化 多子群 蚁群算法 协同航迹规划 

分 类 号：V279[航空宇航科学与技术—飞行器设计]