北京航空航天大学学报 ›› 2010, Vol. 36 ›› Issue (1): 6-9.

• 论文 • 上一篇    下一篇

基于引导型人工免疫算法的最优Lambert变轨

彭 坤, 徐世杰, 陈 统   

  1. 北京航空航天大学 宇航学院, 北京 100191
  • 收稿日期:2009-08-10 出版日期:2010-01-31 发布日期:2010-09-13
  • 作者简介:彭 坤(1984-),男,湖北鄂州人,博士生,bhkpeng@126.com.
  • 基金资助:

    国家自然科学基金资助项目(10702003)

Optimal Lambert transfer based on guiding artificial immune algorithm

Peng Kun, Xu Shijie, Chen Tong   

  1. School of Astronautics, Beijing University of Aeronautics and Astronautics, Beijing 100191, China
  • Received:2009-08-10 Online:2010-01-31 Published:2010-09-13

摘要: 主要研究了燃料最省的Lambert双脉冲变轨问题.首先对普适变量法进行改进以避免奇异,并将其用于Lambert双脉冲变轨问题的求解.然后针对只给定初始时刻追踪航天器和目标航天器的轨道要素及总时间约束的交会问题,引入调相时间的概念,并将其和转移时间作为Lambert变轨的优化变量.最后采用引导型人工免疫算法GAIA(Guiding Artificial Immune Algorithm)对该优化问题进行寻优.仿真算例表明,与自适应遗传算法AGA(Adaptive Genetic Algorithm)相比,GAIA具有更强的寻优能力和更快的寻优速度,从而验证了GAIA用于最优Lambert变轨的有效性.

Abstract: The optimization with cost function of fuel consumption minimum for Lambert two-impulse transfer was studied. Firstly, the universal variables method was modified to avoid singularity, and it was used to solve the Lambert two-impulse transfer problem. Then for the rendezvous problem with only orbit elements fixed of a chase spacecraft and a target spacecraft in initial time, the concept of phase time was introduced under the restriction of the total time. Both the phase time and transfer time were considered as variables to be optimized in the Lambert transfer. Finally, a guiding artificial immune algorithm (GAIA) was applied to solve this optimization problem. Simulation results show that, compared with adaptive genetic algorithm (AGA), GAIA has stronger search capacity and quicker search speed, which validates the effectiveness of GAIA for the optimal Lambert transfer.

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