计算机工程与应用 ›› 2010, Vol. 46 ›› Issue (32): 224-227.DOI: 10.3778/j.issn.1002-8331.2010.32.062

• 工程与应用 • 上一篇    下一篇

基于免疫粒子群算法的多UCAV协同任务分配

有 伟1,王社伟1,陶 军1,2   

  1. 1.空军航空大学 航空控制工程系,长春 130022
    2.吉林大学 通信工程学院,长春 130025
  • 收稿日期:2009-03-23 修回日期:2009-05-13 出版日期:2010-11-11 发布日期:2010-11-11
  • 通讯作者: 有 伟

Multi-UCAV cooperative task assignment by immune particle swarm algorithm

YOU Wei1,WANG She-wei1,TAO Jun1,2   

  1. 1.Aviation Control Engineering Department,Aviation University of Air Force,Changchun 130022,China
    2.College of Communication Engineering,Jilin University,Changchun 130025,China
  • Received:2009-03-23 Revised:2009-05-13 Online:2010-11-11 Published:2010-11-11
  • Contact: YOU Wei

摘要: 任务分配问题是多UCAV协同控制的关键和有效保证。综合考虑问题的多规划指标和多类复杂约束条件,建立了基于多目标整数规划的协同多任务分配模型。通过模拟生物免疫系统的免疫特征和运行机制,并将粒子群优化作为算法的局部搜索算子,设计了一种适用于问题求解的免疫粒子群算法,使算法同时具有人工免疫算法种群多样性好、粒子群优化局部搜索能力和进化方向性强等特点。仿真实验表明该方法具有良好的优化效果和时间特性,可较好地解决多UCAV协同任务分配问题。

Abstract: Task assignment is the key and effective guarantee of multi-UCAV cooperative control.Based on multi-object optimization,the formulation of cooperative task assignment is presented,which takes multi-programming indexes and multi-variety complex constraints in account.By simulating the immune character and operated mechanism of biological immune system,and making the PSO for the local search operator of the AIA,the IPSO algorithm fit for solution is designed,the algorithm simultaneous has good variety and strong local search.Simulation results indicate that the method has good optimal effect and time performance.The algorithm can solve the problem of multi-UCAV cooperative task assignment effectively.

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