Nepal, Ayush Mani und Prat i Sala, Arnau und Höflinger, Kilian Johann und Gerndt, Andreas und Lüdtke, Daniel (2020) Modeling and Simulation of a Spacecraft Payload Hardware Using Machine Learning Techniques. In: Accelerating Space Commerce, Exploration, and New Discovery Conference, ASCEND 2020. ASCEND 2020, 2020-11-16 - 2020-11-18, Online. doi: 10.2514/6.2020-4219. ISBN 9781624106088.
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Kurzfassung
Space systems are complex and consist of multiple subsystems. Research and development teams of such complex systems are usually distributed among various institutions and space agencies. This affects the quality of the On-board Software (OBSW) since testing it without having all required subsystems at the software development site can be troublesome. In this paper, we present a data-driven method which can be used to synthesize parts of a system or even an entire system as a black-box model. We exploit the data collected from the real hardware to derive a model using a Machine Learning (ML) algorithm. The proposed model can easily be distributed among development teams and is dedicated to emulate the system for testing the OBSW.
elib-URL des Eintrags: | https://elib.dlr.de/137571/ | ||||||||||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Vortrag) | ||||||||||||||||||||||||
Titel: | Modeling and Simulation of a Spacecraft Payload Hardware Using Machine Learning Techniques | ||||||||||||||||||||||||
Autoren: |
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Datum: | 2 November 2020 | ||||||||||||||||||||||||
Erschienen in: | Accelerating Space Commerce, Exploration, and New Discovery Conference, ASCEND 2020 | ||||||||||||||||||||||||
Referierte Publikation: | Nein | ||||||||||||||||||||||||
Open Access: | Ja | ||||||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||||||
In SCOPUS: | Ja | ||||||||||||||||||||||||
In ISI Web of Science: | Nein | ||||||||||||||||||||||||
DOI: | 10.2514/6.2020-4219 | ||||||||||||||||||||||||
ISBN: | 9781624106088 | ||||||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||||||
Stichwörter: | modeling and simulation, machine learning, neural networks, LSTM, artificial intelligence (AI), data-driven, physical system modeling | ||||||||||||||||||||||||
Veranstaltungstitel: | ASCEND 2020 | ||||||||||||||||||||||||
Veranstaltungsort: | Online | ||||||||||||||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||||||||||||||
Veranstaltungsbeginn: | 16 November 2020 | ||||||||||||||||||||||||
Veranstaltungsende: | 18 November 2020 | ||||||||||||||||||||||||
Veranstalter : | AIAA | ||||||||||||||||||||||||
HGF - Forschungsbereich: | keine Zuordnung | ||||||||||||||||||||||||
HGF - Programm: | keine Zuordnung | ||||||||||||||||||||||||
HGF - Programmthema: | keine Zuordnung | ||||||||||||||||||||||||
DLR - Schwerpunkt: | keine Zuordnung | ||||||||||||||||||||||||
DLR - Forschungsgebiet: | keine Zuordnung | ||||||||||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | keine Zuordnung, R - Vorhaben SISTEC (alt) | ||||||||||||||||||||||||
Standort: | Braunschweig | ||||||||||||||||||||||||
Institute & Einrichtungen: | Institut für Softwaretechnologie > Software für Raumfahrtsysteme und interaktive Visualisierung Institut für Softwaretechnologie | ||||||||||||||||||||||||
Hinterlegt von: | Nepal, Ayush Mani | ||||||||||||||||||||||||
Hinterlegt am: | 16 Dez 2020 11:33 | ||||||||||||||||||||||||
Letzte Änderung: | 13 Nov 2024 15:25 |
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