引用本文:贺东雷,冯小恩,雷明佳,江飞龙,董诗音,李玉庆.面向深空探测任务的实数遗传编码多星任务规划算法[J].控制理论与应用,2019,36(12):2055~2064.[点击复制]
HE Dong-lei,FENG Xiao-en,LEI Ming-jia,JIANG Fei-long,DONG Shi-yin,LI Yu-qing.Real genetic coding multi-star task planning algorithm for deep space exploration mission[J].Control Theory and Technology,2019,36(12):2055~2064.[点击复制]
面向深空探测任务的实数遗传编码多星任务规划算法
Real genetic coding multi-star task planning algorithm for deep space exploration mission
摘要点击 1397  全文点击 605  投稿时间：2019-06-28  修订日期：2019-12-08
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DOI编号  10.7641/CTA.2019.90492
  2019,36(12):2055-2064
中文关键词  深空探测  卫星任务规划  遗传算法  实数编码
英文关键词  space observation  satellite mission planning  genetic algorithm  real number coding
基金项目  深空探测着陆与返回控制技术国防重点学科实验室开放基金
作者单位邮编
贺东雷 北京空间飞行器总体设计部 100094
冯小恩* 哈尔滨工业大学深空探测基础研究中心 150001
雷明佳 哈尔滨工业大学深空探测基础研究中心 
江飞龙 哈尔滨工业大学深空探测基础研究中心 
董诗音 哈尔滨工业大学深空探测基础研究中心 
李玉庆 哈尔滨工业大学深空探测基础研究中心 
中文摘要
      针对多星任务规划问题,综合考虑卫星对目标时间窗口、卫星姿态机动以及卫星工作能耗等约束条件,建立了多星任务规划问题模型,针对常规01编码在进行大规模卫星任务规划时,存在的编码长度过长等问题,提出了一种基于实数编码方式的遗传算法,以求解多星任务规划问题。该算法采用了一种以目标为染色体的实数编码方式,相比传统的以时间窗口为染色体的01编码方式,缩短了染色体长度,可有效提高算法的求解效率。通过仿真算例分析,验证了基于实数编码的遗传算法对求解多星任务规划问题的正确性、合理性和有效性,并将其与基于传统01编码方式的遗传算法进行对比分析,其结果表明基于实数编码方式的遗传算法在寻优能力和计算速度上具有明显优势,这为求解多星任务规划问题提供了一种新的思路和方法。
英文摘要
      For the multi-star mission planning problem, considering the constraint conditions of satellites on target time window, satellite attitude maneuvering, and satellite work energy consumption, a multi-star mission planning model is established. When the conventional 01 code is used for large-scale satellite mission planning, there are problems such as excessive code length, etc. So a real-coded genetic algorithm is proposed to solve multi-star mission planning problem. The algorithm uses a real number encoding method with the target as a chromosome. Compared with the traditional 01 encoding method in which the time window is a chromosome, the length of the chromosome is shortened, and the efficiency of the algorithm can be effectively improved. Through simulation example analysis, the correctness, rationality and effectiveness of the real-coded genetic algorithm for solving multi-star task planning problems are verified. The genetic algorithm based on the traditional 01-coded method is compared and analyzed. The results show that The genetic algorithm based on the real number coding method has obvious advantages both in the optimization ability and the calculation speed, which provides a new idea and method for solving multi-star task planning problems.