航空学报 > 2023, Vol. 44 Issue (23): 628462-628462   doi: 10.7527/S1000-6893.2023.28462

可重复使用运载火箭技术专栏

运载火箭动力着陆段制导控制方法综述与展望

何林坤1, 薛文超2,3(), 张冉1, 李惠峰1   

  1. 1.北京航空航天大学 宇航学院,北京 100191
    2.中国科学院 数学与系统科学研究院,北京 100190
    3.中国科学院大学 数学科学学院,北京 100049
  • 收稿日期:2023-01-03 修回日期:2023-01-28 接受日期:2023-05-25 出版日期:2023-12-15 发布日期:2023-06-02
  • 通讯作者: 薛文超 E-mail:wenchaoxue@amss.ac.cn
  • 基金资助:
    国家自然科学基金(62122083);中国科学院青年创新促进会资助

Guidance and control for powered descent and landing of launch vehicles: Overview and outlook

Linkun HE1, Wenchao XUE2,3(), Ran ZHANG1, Huifeng LI1   

  1. 1.School of Astronautics,Beihang University,Beijing 100191,China
    2.Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing 100190,China
    3.School of Mathematical Sciences,University of Chinese Academy of Sciences,Beijing 100049,China.
  • Received:2023-01-03 Revised:2023-01-28 Accepted:2023-05-25 Online:2023-12-15 Published:2023-06-02
  • Contact: Wenchao XUE E-mail:wenchaoxue@amss.ac.cn
  • Supported by:
    National Natural Science Foundation of China(62122083);Youth Innovation Promotion Association of Chinese Academy of Science

摘要:

可重复使用运载火箭能够大幅降低进入空间的成本,是下一代航天运输系统的重要组成部分,而动力着陆段是实现可重复使用运载火箭回收的关键。对现有运载火箭动力着陆段的制导控制方法进行了综述,在对现有方法进行分析的基础上提出了一种模块化协作设计,并对人工智能方法在制导控制中的应用进行了展望。首先建立了运载火箭动力着陆段制导控制的整体模型,归纳了常用指标及约束集合,并分析了制导控制设计需解决的问题。然后,对现有的主要制导控制方法,即解析制导方法、轨迹优化制导方法、基于机器学习的制导方法、姿态控制方法及制导控制协作方法等进行了综述,通过分析所考虑的运动方程模型、约束及性能指标等对主要方法进行了较全面的比较,并进一步针对不确定模型及干扰下的制导控制综合目标优化问题提出了一种模块化智能协作方法。最后,对动力着陆段制导控制方法的发展趋势进行了总结,并对人工智能方法与动力着陆段制导控制方法的结合进行了展望。

关键词: 可重复使用运载火箭, 动力着陆制导, 动力着陆姿态控制, 制导控制协作, 人工智能

Abstract:

The cost of entrance into space can be significantly reduced by the application of reusable launch vehicle, which is an important component of the next-generation space transportation system. For reusable launch vehicles, the powered descent and landing phase is the key to successful recovery. Existing guidance and control methods for powered descent and landing are reviewed. Based on the analysis of existing methods, an intelligent modular integration method for guidance and control is proposed, and an outlook on the application of artificial intelligence methods in guidance and control of powered descent and landing is presented. Firstly, a complete model for guidance and control of powered descent and landing, along with the widely considered objectives and constraints, is established, and the main difficulties for guidance and control design are analyzed. Thereafter, existing guidance and control methods for powered descent and landing, i.e., the analytical guidance method, trajectory optimization based guidance method, learning based guidance method, the attitude control method, and the guidance and control integration method, are reviewed, and a comprehensive comparison of these methods is made by analyzing the considered equations of motion model, constraints, and objectives. Furthermore, a modular intelligent integration method is proposed for optimizing comprehensive objectives in guidance and control under uncertain models and disturbances. Finally, the development trends of guidance and control methods of powered descent and landing are summarized, and an outlook on the combination of artificial intelligence methods and guidance and control methods of powered descent and landing is given.

Key words: reusable launch vehicle, powered descent and landing guidance, powered descent and landing attitude control, integrated guidance and control, artificial intelligence

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