Kalman filter and satellite attitude control system analytical design
Kalman filter and satellite attitude control system analytical design
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Full item details
- creativework.keywords - en
- Analytical design
- Dynamic system
- Satellite attitude control system
- Kalman filter
- Controller
- Estimator
- Filter
- White noise
- Optimal estimation and control
- dc.contributor.author
- Kim, Yuri
- dc.date.accessioned
- 2023-05-23T19:24:02Z
- dc.date.available
- 2023-05-23T19:24:02Z
- dc.date.issued
- 2020-09-14
- dc.description.abstract - en
- Certain robust form of suboptimal Kalman-Busy Filter (KBF), with Bounded Grows of Memory (FBGM) is considered for satellite Attitude Control System (ACS) design purposes. At the first step of the design, at the preliminary (conceptual model – CM or low fidelity model - LFM) design it can be used to synthesize the system state estimator/observer and the controller and to evaluate system feasibility and potentially achievable performance. Further steps of the design, take into account some realistic constrains and restrictions, and develop this LFM, by adding more detail elements, to complex, non-linear and not-stationary high fidelity model (HFM). This model (HFM) should be analyzed from the System Engineering point of view, during design review, prototyping, manufacturing, testing and qualification. However, the CM, as the basic reference, still keeps its significance to the end of the system life time cycle. If the conceptual design was performed professionally by the experienced developer, it is usually sound and robust, and the LFM can be considered as a generic model that would not be drastically changed developing the HFM model. Rather some additional elements and constrains would be introduced, but not making unfit previous analysis and the results. More than that, with small additions synthesized at the conceptual design phase state estimator and controller can be directly implemented in the Flight System. However, even experienced specialist is not assured against mistakes and misinterpretations sometimes leading to wrong solutions. Also new developers (beginners) can be involved, students should have a solid methodology based on an objective criteria rather than on the tutor experience and intuition. All this presents the actuality of the consideration presented below. It is in the scope of the linear, time invariant systems under assumptions of the linear KBF theory. If these assumptions are applicable then presented results can be implemented or, at least used as a reference, to guide developers through the system developing process.
- dc.identifier.doi
- https://doi.org/10.1504/IJSPACESE.2020.109749
- dc.identifier.uri
- https://open-science.canada.ca/handle/123456789/299
- dc.language.iso
- en
- dc.publisher
- Inderscience Publishers
- dc.rights - en
- None
- dc.rights - fr
- Aucune
- dc.subject - en
- Science and technology
- dc.subject - fr
- Sciences et technologie
- dc.subject.en - en
- Science and technology
- dc.subject.fr - fr
- Sciences et technologie
- dc.title - en
- Kalman filter and satellite attitude control system analytical design
- dc.type - en
- Article
- dc.type - fr
- Article
- local.article.journalissue
- 1
- local.article.journaltitle
- International Journal of Space Science and Engineering
- local.article.journalvolume
- 6
- local.pagination
- 82-103
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