Technical Papers
Nov 17, 2016

Parameter Identification–Based Attitude Stabilization Control of Spacecraft with Multiaccessories during Orbital Maneuver

Publication: Journal of Aerospace Engineering
Volume 30, Issue 3

Abstract

Targeted at one kind of on-orbit servicing spacecraft that contains flue containers, momentum actuators, space manipulators, and captured unknown objects, a specific attitude control problem during orbital maneuvers is under investigation in this paper. To overcome strong uncertainties during the onboard service, a parameter-identification algorithm is developed to estimate all inertial parameters of each part of the spacecraft system, and the identification results are obtained based solely on the measurement of the inertial navigation system. Therefore, the disturbance from the torque coupling of the orbital engine can be thus effectively compensated. Based on the identified parameters, the attitude stabilization problem is taken into practical consideration to tackle the strong influence from the orbital engine disturbance of concern. In order to specifically suppress the disturbance, a hybrid control strategy based on the momentum actuators and thrusters is proposed, which not only provides better precision than the conventional thruster-based method but also guarantees the momentum actuators against the momentum saturation issues. Numerical simulations are conducted to verify the effectiveness of the proposed algorithms.

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Acknowledgments

This work is supported by National Natural Science Foundation (NNSF) of China under Grant Nos. 51407011, 11372034, and 51207145.

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Go to Journal of Aerospace Engineering
Journal of Aerospace Engineering
Volume 30Issue 3May 2017

History

Received: Jan 29, 2016
Accepted: Aug 1, 2016
Published online: Nov 17, 2016
Discussion open until: Apr 17, 2017
Published in print: May 1, 2017

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Authors

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Xiangdong Liu, Ph.D. [email protected]
Professor, School of Automation and Chinese National Key Laboratory of Complex System Intelligent Control and Decision, Beijing Institute of Technology, Beijing 100081, China. E-mail: [email protected]
Xing Xin, Ph.D. [email protected]
School of Automation, Beijing Institute of Technology, Beijing 100081, China; presently, Beijing Institute of Electronic System Engineering, Beijing 100854, China. E-mail: [email protected]
Associate Professor, School of Automation and Chinese National Key Laboratory of Complex System Intelligent Control and Decision, Beijing Institute of Technology, Beijing 100081, China (corresponding author). ORCID: https://orcid.org/0000-0003-1166-9482. E-mail: [email protected]
Yongzhi Sheng, Ph.D. [email protected]
Lecturer, School of Automation and Chinese National Key Laboratory of Complex System Intelligent Control and Decision, Beijing Institute of Technology, Beijing 100081, China. E-mail: [email protected]
Zhen Chen, Ph.D. [email protected]
Associate Professor, School of Automation and Chinese National Key Laboratory of Complex System Intelligent Control and Decision, Beijing Institute of Technology, Beijing 100081, China. E-mail: [email protected]

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