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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2021, Vol. 42 ›› Issue (4): 524201-524201.doi: 10.7527/S1000-6893.2020.24201

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Spacecraft guidance and control based on artificial intelligence: Review

HUANG Xuxing1, LI Shuang1, YANG Bin1, SUN Pan1, LIU Xuewen1, LIU Xinyan2   

  1. 1. College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China;
    2. Beijing Institute of Control Engineering, Beijing 100190, China
  • Received:2020-05-08 Revised:2020-06-04 Published:2020-07-06
  • Supported by:
    Technology and Industry Bureau of Civil Aerospace "13th Five-Year" preliminary Research Project (D010305); Funded by Science and Technology on Space Intelligent Control Laboratory (HTKJ2019KL502012,KGJZDSYS-2018-11)

Abstract: Spacecraft guidance and control technology is one of the key technologies to ensure successful implementation of space missions. Currently, the strong nonlinearity of dynamic models and the uncertainty of parameters restrict the development of high-precision attitude and orbit control technology, while the system failure determines the success or failure of the spacecraft attitude and orbit control. The new generation of artificial intelligence technology represented by machine learning shows tremendous potential in the field of spacecraft guidance and control. This paper first summarizes the research development and application status of trajectory guidance and attitude control based on artificial intelligence technology, and analyzes the development trend of spacecraft trajectory planning, attitude control, fault diagnosis and fault-tolerant control technology. Then, from the four aspects of robust trajectory planning, adaptive attitude control, rapid fault diagnosis, and adaptive fault tolerance control, the key technologies of spacecraft attitude and orbit control suitable for future space missions are reviewed. Finally, according to the challenges faced by the application of intelligent navigation and control technology, corresponding development suggestions are proposed in terms of strategy construction, algorithm optimality, training and technical verification.

Key words: artificial intelligence, trajectory guidance, attitude control, intelligence guidance, adaptive guidance, fault diagnosis, fault tolerant control

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