基于粒子群优化的无人战斗机编队任务协调方法研究  

Study on uninhabited combat air vehicle formation tasks scheduling method based on particle swarm optimization algorithm

作　　者：张雷[1,2] 王道波[1] 高宇辉 段海滨[4] 

机构地区：[1]南京航空航天大学自动化学院,江苏南京210016 [2]空军装备研究院通信导航与指挥自动化研究所,北京100085 [3]航天指挥控制中心,北京100094 [4]北京航空航天大学自动化科学与电气工程学院,北京100083

出　　处：《系统工程与电子技术》2009年第2期439-442,共4页Systems Engineering and Electronics

基　　金：国家航空科学基金资助课题(2006ZC51039)

摘　　要：执行任务时多无人机之间的任务协调是保证无人机具备协同工作能力并且顺利完成任务的关键。将无人战斗机编队的协调过程看成一种动态的任务分配过程,建立任务协调模型,分析任务协调问题的粒子初始化和寻优方法,编写基于粒子群优化算法的任务协调问题程序。对粒子群优化算法参数对任务协调方案的影响进行了仿真验证,结果表明此方法得出的方案合理有效可以满足无人战斗机任务协调问题的要求。When multi uninhabited combat air vehicles （UCAVs） are executing their tasks, their tasks scheduling is a key issue that UCAVs have interoperability and can complete their tasks. If task scheduling was assumed as a dynamic task allocation process, the scheduling model is built. Then an algorithm based on parti- cle swarm optimization （PSO） is introduced, when the initialized particles were constructed, the task scheduling program based on PSO can be acquired. The influences of PSO parameters on scheduling results are validated, and the simulation shows that the task scheduling results are valid and conform to the requirements of task scheduling problems.

关 键 词：无人战斗机 任务协调 目标分配 粒子群优化 

分 类 号：TP301[自动化与计算机技术—计算机系统结构] O225[自动化与计算机技术—计算机科学与技术]