Research on fault detection and principal component analysis for spacecraft feature extraction based on kernel methods
Author:
Affiliation:
1. State Key Laboratory of Astronautic Dynamics, Xi’an Satellite Control Center , Xi’an , China
2. School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi’an Jiaotong University , Xi’an , China
Abstract
Publisher
Walter de Gruyter GmbH
Subject
Space and Planetary Science,Astronomy and Astrophysics
Link
https://www.degruyter.com/document/doi/10.1515/astro-2022-0194/pdf
Reference17 articles.
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2. Bonfe M, Castaldi P, Geri W, Simani S. 2006. Fault detection and isolation for on-board sensors of a general aviation aircraft. Int J Adapt Control. 20(8):381–408.
3. Flores-Abad A, Ma O, Pham K, Ulrich S. 2014. A review of space robotics technologies for on-orbit servicing. Prog Aerosp. 68(12):1–26.
4. Gao C, Duan G. 2014. Fault diagnosis and fault tolerant control for nonlinear satellite attitude control systems. Aerosp Sci Technol. 33(1):9–15.
5. Gueddi I, Nasri O, Benothman K, Dague P 2017. Fault Detection and Isolation of spacecraft thrusters using an extended principal component analysis to interval data. Int J Control Autom. 15(2):776–789.
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2. Advanced fault detection and diagnosis in spacecraft attitude control systems: Current state and challenges;Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering;2023-02-17
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