资源强耦合下改进遗传测控调度方法  

Improved genetic method for satellite TT&C scheduling under strong resource coupling

作　　者：尹霞 韩笑冬[3] 李朝玉 徐瑞[1,2] YIN Xia;HAN Xiaodong;LI Zhaoyu;XU Rui(School of Aerospace Engineering,Beijing Institute of Technology,Beijing 100081,China;Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration(Beijing Institute of Technology),Ministry of Industry and Information Technology,Beijing 100081,China;Institute of Telecommunication and Navigation Satellite,China Academy of Space Technology,Beijing 100094,China)

机构地区：[1]北京理工大学宇航学院,北京100081 [2]深空自主导航与控制工信部重点实验室(北京理工大学),北京100081 [3]中国空间技术研究院通信与导航卫星总体部,北京100094

出　　处：《中国空间科学技术(中英文)》2025年第1期59-68,共10页Chinese Space Science and Technology

基　　金：国家自然科学基金青年科学基金(62006019);青年人才托举工程(2022QNRC001)。

摘　　要：随着航天器智能化发展,航天器数量增加、任务数量及复杂度增加导致智能航天器测控需求增加,测控调度资源耦合程度增大,求解空间维度呈现指数型增长,然而现有方法对资源耦合问题的研究较少且调度效率无法满足任务需求。针对上述问题,提出了资源强耦合下改进遗传测控调度方法,首先对多星测控调度问题进行建模,分析测控调度问题中的资源耦合性,定义适应度函数及哈希表类型的冲突字典;在遗传算法基础上设计了任务序列与收益并存的二维染色体编码形式,提出了优势任务相关的初始种群多线程并行生成方法,引导优化解的探索方向;设计了并行顺序解耦的交叉、变异算子,在冲突字典的辅助下,按照基因顺序实现高效实时的资源耦合处理,最终通过迭代得到测控调度解序列。通过多组仿真试验结果,证明了该方法均具有良好的收敛性,且与常规遗传算法对比试验中,该方法任务收益平均提高了21.31%,同时运行时间平均降低了24.36%,进而验证了资源强耦合下改进遗传测控方法的高效性,为智能航天器运行及管理提供技术支撑。With the development of spacecraft intelligence,an increase in the number of spacecraft and the complexity of missions lead to an increased demand for intelligent spacecraft measurement and control.The coupling degree of satellite TT&C scheduling resources grows,and the solution space dimension expands exponentially.However,existing methods limit the research on resource coupling issues,and the scheduling efficiency can not meet mission requirements.Aiming at the above problems,an improved genetic method for satellite TT&C scheduling under strong resource coupling is proposed.Firstly,the multi-satellite TT&C scheduling problem is modeled,and then the resource coupling in satellite TT&C scheduling problem is analyzed,with the objective function and the hash table type dictionary of conflicting tasks defined.On the basis of genetic algorithm,a two-dimensional chromosome encoding form is designed that combines task sequences and benefits,and a multi-thread generation method is established for initializing the population with advantageous tasks.Multi-thread crossover and mutation operators for sequential decoupling are designed to efficiently process resource coupling information in realtime according to gene order with the assistance of the conflicting-task dictionary.Finally,a scheduling solution of task sequence is obtained through iteration.The results of three simulation experiments demonstrate that this method has good convergence.Compared with the conventional genetic algorithm experiments,the average task benefit of this method increases by 21.31%,and the average runtime decreases by 24.36%.This validates the efficiency of the improved genetic method for satellite TT&C scheduling under strong resource coupling,providing technical support for the operation and management of intelligent spacecraft.

关 键 词：测控调度 遗传算法 资源耦合 多星测控 任务规划 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]