Disturbance-Learning-Based Attitude Maneuvering Control for Spacecraft Under Strong Composite Disturbances

Hao Teng; Jiaao Wu; Yixuan Zhang; Qiang Xu; Dong Zhao; Zhixuan Lian

doi:10.1109/IECON58223.2025.11221703

Disturbance-Learning-Based Attitude Maneuvering Control for Spacecraft Under Strong Composite Disturbances

Hao Teng
, Jiaao Wu
, Yixuan Zhang
, Qiang Xu
, Dong Zhao^*
, Zhixuan Lian^*

^*Corresponding author for this work

Beihang University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Attitude maneuvers of spacecraft inevitably introduce composite disturbances such as center of mass variations, structural flexible vibrations, and actuator uncertainties. These disturbances are strongly coupled with the system's states and control inputs, forming a composite disturbance profile that severely impacts attitude tracking and pointing accuracy. To address this challenge, a maneuvering control scheme based on composite disturbance learning is proposed. First, a deep coupled spacecraft attitude dynamics model is developed to capture the influence and transmission mechanisms of composite disturbances. Then, a composite controller incorporating a disturbance learning observer is designed to perform online modeling and real-time compensation of these disturbances. The effectiveness of the proposed approach is validated through experiment studies.

Original language	English
Title of host publication	IECON 2025 - 51st Annual Conference of the IEEE Industrial Electronics Society
Publisher	IEEE Computer Society
ISBN (Electronic)	9798331596811
DOIs	https://doi.org/10.1109/IECON58223.2025.11221703
State	Published - 2025
Event	51st Annual Conference of the IEEE Industrial Electronics Society, IECON 2025 - Madrid, Spain Duration: 14 Oct 2025 → 17 Oct 2025

Publication series

Name	IECON Proceedings (Industrial Electronics Conference)
ISSN (Print)	2162-4704
ISSN (Electronic)	2577-1647

Conference

Conference	51st Annual Conference of the IEEE Industrial Electronics Society, IECON 2025
Country/Territory	Spain
City	Madrid
Period	14/10/25 → 17/10/25

Keywords

Spacecraft maneuvering control
composite controller
composite multi-source disturbances
disturbance learning observer

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10.1109/IECON58223.2025.11221703

Cite this

Teng, H., Wu, J., Zhang, Y., Xu, Q., Zhao, D., & Lian, Z. (2025). Disturbance-Learning-Based Attitude Maneuvering Control for Spacecraft Under Strong Composite Disturbances. In IECON 2025 - 51st Annual Conference of the IEEE Industrial Electronics Society (IECON Proceedings (Industrial Electronics Conference)). IEEE Computer Society. https://doi.org/10.1109/IECON58223.2025.11221703

@inproceedings{e363cc7a509647a490a4ffe56dc78356,

title = "Disturbance-Learning-Based Attitude Maneuvering Control for Spacecraft Under Strong Composite Disturbances",

abstract = "Attitude maneuvers of spacecraft inevitably introduce composite disturbances such as center of mass variations, structural flexible vibrations, and actuator uncertainties. These disturbances are strongly coupled with the system's states and control inputs, forming a composite disturbance profile that severely impacts attitude tracking and pointing accuracy. To address this challenge, a maneuvering control scheme based on composite disturbance learning is proposed. First, a deep coupled spacecraft attitude dynamics model is developed to capture the influence and transmission mechanisms of composite disturbances. Then, a composite controller incorporating a disturbance learning observer is designed to perform online modeling and real-time compensation of these disturbances. The effectiveness of the proposed approach is validated through experiment studies.",

keywords = "Spacecraft maneuvering control, composite controller, composite multi-source disturbances, disturbance learning observer",

author = "Hao Teng and Jiaao Wu and Yixuan Zhang and Qiang Xu and Dong Zhao and Zhixuan Lian",

note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 51st Annual Conference of the IEEE Industrial Electronics Society, IECON 2025 ; Conference date: 14-10-2025 Through 17-10-2025",

year = "2025",

doi = "10.1109/IECON58223.2025.11221703",

language = "英语",

series = "IECON Proceedings (Industrial Electronics Conference)",

publisher = "IEEE Computer Society",

booktitle = "IECON 2025 - 51st Annual Conference of the IEEE Industrial Electronics Society",

address = "美国",

}

Teng, H, Wu, J, Zhang, Y, Xu, Q, Zhao, D & Lian, Z 2025, Disturbance-Learning-Based Attitude Maneuvering Control for Spacecraft Under Strong Composite Disturbances. in IECON 2025 - 51st Annual Conference of the IEEE Industrial Electronics Society. IECON Proceedings (Industrial Electronics Conference), IEEE Computer Society, 51st Annual Conference of the IEEE Industrial Electronics Society, IECON 2025, Madrid, Spain, 14/10/25. https://doi.org/10.1109/IECON58223.2025.11221703

Disturbance-Learning-Based Attitude Maneuvering Control for Spacecraft Under Strong Composite Disturbances. / Teng, Hao; Wu, Jiaao; Zhang, Yixuan et al.
IECON 2025 - 51st Annual Conference of the IEEE Industrial Electronics Society. IEEE Computer Society, 2025. (IECON Proceedings (Industrial Electronics Conference)).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Disturbance-Learning-Based Attitude Maneuvering Control for Spacecraft Under Strong Composite Disturbances

AU - Teng, Hao

AU - Wu, Jiaao

AU - Zhang, Yixuan

AU - Xu, Qiang

AU - Zhao, Dong

AU - Lian, Zhixuan

PY - 2025

Y1 - 2025

N2 - Attitude maneuvers of spacecraft inevitably introduce composite disturbances such as center of mass variations, structural flexible vibrations, and actuator uncertainties. These disturbances are strongly coupled with the system's states and control inputs, forming a composite disturbance profile that severely impacts attitude tracking and pointing accuracy. To address this challenge, a maneuvering control scheme based on composite disturbance learning is proposed. First, a deep coupled spacecraft attitude dynamics model is developed to capture the influence and transmission mechanisms of composite disturbances. Then, a composite controller incorporating a disturbance learning observer is designed to perform online modeling and real-time compensation of these disturbances. The effectiveness of the proposed approach is validated through experiment studies.

AB - Attitude maneuvers of spacecraft inevitably introduce composite disturbances such as center of mass variations, structural flexible vibrations, and actuator uncertainties. These disturbances are strongly coupled with the system's states and control inputs, forming a composite disturbance profile that severely impacts attitude tracking and pointing accuracy. To address this challenge, a maneuvering control scheme based on composite disturbance learning is proposed. First, a deep coupled spacecraft attitude dynamics model is developed to capture the influence and transmission mechanisms of composite disturbances. Then, a composite controller incorporating a disturbance learning observer is designed to perform online modeling and real-time compensation of these disturbances. The effectiveness of the proposed approach is validated through experiment studies.

KW - Spacecraft maneuvering control

KW - composite controller

KW - composite multi-source disturbances

KW - disturbance learning observer

UR - https://www.scopus.com/pages/publications/105024700403

U2 - 10.1109/IECON58223.2025.11221703

DO - 10.1109/IECON58223.2025.11221703

M3 - 会议稿件

AN - SCOPUS:105024700403

T3 - IECON Proceedings (Industrial Electronics Conference)

BT - IECON 2025 - 51st Annual Conference of the IEEE Industrial Electronics Society

PB - IEEE Computer Society

T2 - 51st Annual Conference of the IEEE Industrial Electronics Society, IECON 2025

Y2 - 14 October 2025 through 17 October 2025

ER -

Disturbance-Learning-Based Attitude Maneuvering Control for Spacecraft Under Strong Composite Disturbances

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