计算机工程 ›› 2008, Vol. 34 ›› Issue (7): 178-180.doi: 10.3969/j.issn.1000-3428.2008.07.063

• 人工智能及识别技术 • 上一篇    下一篇

改进粒子群算法在UCAV航路规划中的应用

叶 文1,朱爱红2,范洪达1   

  1. (1. 海军航空工程学院兵器科学与技术系,烟台 264001;2. 海军航空工程学院训练部,烟台 264001)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2008-04-05 发布日期:2008-04-05

Application of Improved Particle Swarm Optimization Algorithm in UCAV Path Planning

YE Wen1, ZHU Ai-hong2, FAN Hong-da1   

  1. (1. Department of Ordnance Science and Technology, Naval Aeronautic Engineering Academy, Yantai 264001; 2. Department of Training, Naval Aeronautic Engineering Academy, Yantai 264001)
  • Received:1900-01-01 Revised:1900-01-01 Online:2008-04-05 Published:2008-04-05

摘要: 针对在无人作战飞机(UCAV)航路规划中存在的计算复杂和收敛性等问题,该文利用标准粒子群算法原理,在算法搜索过程中引入变异算子,克服了标准算法易陷入局部极值点的不足。利用一组正弦波曲线来构造一个粒子,通过对正弦波个数和幅值的限制,使该方法得到的飞行航路严格经过起始点和目标点,而且满足UCAV的机动性能要求。仿真结果表明该方法简便可行,粒子能较快地收敛于全局最佳航路。

关键词: 无人作战飞机, 粒子群优化, 变异算子, 航路规划

Abstract: For the calculation complexity and the convergence in Unmanned Combat Aerial Vehicle(UCAV) path planning, based on the study on the principles of traditional Particle Swarm Optimization(PSO), mutation operator is presented during the searching process in order to prevent from getting into the local optimum. This paper uses a group of sine waves to construct a parameter, and restricts the number and swing of sine waves. The optimal route can pass the start point and the target point precisely, and is feasible applying to UCAV. Simulation result shows that the method is effective.

Key words: Unmanned Combat Aerial Vehicle(UCAV), Particle Swarm Optimization(PSO), mutation operator, path planning

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