@inproceedings{bb2cd021c0c34ba8a319542d73021d3d,
title = "Learning-based Attitude Takeover Control for Noncooperative Space Targets with Unknown Dynamics",
abstract = "In this paper, we address the problem of post-capture combined spacecraft takeover control for a noncooperative space target with partial constraints and target maneuvering. The real-time inertia tensors identification is avoided, while only the I/O data collected during the on-board operation are utilized to learn a Gaussian process regression model to significantly decrease the system uncertainties. In the meantime, the feedback gains are adaptive with the predicted model confidence. Furthermore, detailed controller design procedures and rigorous theoretical proof of all related closed-loop uniform ultimate bounded (UUB) stability guarantees are provided. Numerical simulations are exhibited to validate the effectiveness of the proposed strategy.",
keywords = "Gaussian process, Machine learning, Noncooperative space target, Post-capture, Takeover control",
author = "Guangfu Ma and Yuhan Liu and Yueyong Lyu and Pengyu Wang",
note = "Publisher Copyright: {\textcopyright} 2021 Technical Committee on Control Theory, Chinese Association of Automation.; 40th Chinese Control Conference, CCC 2021 ; Conference date: 26-07-2021 Through 28-07-2021",
year = "2021",
month = jul,
day = "26",
doi = "10.23919/CCC52363.2021.9549415",
language = "英语",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "2233--2238",
editor = "Chen Peng and Jian Sun",
booktitle = "Proceedings of the 40th Chinese Control Conference, CCC 2021",
address = "美国",
}