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Modeling and Simulation of a Spacecraft Payload Hardware Using Machine Learning Techniques

Nepal, Ayush Mani and Prat i Sala, Arnau and Höflinger, Kilian Johann and Gerndt, Andreas and Lüdtke, Daniel (2020) Modeling and Simulation of a Spacecraft Payload Hardware Using Machine Learning Techniques. In: ASCEND. ASCEND 2020, 16-18 Nov 2020, Online. doi: 10.2514/6.2020-4219. ISBN 978-1-62410-608-8.

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Abstract

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.

Item URL in elib:https://elib.dlr.de/137571/
Document Type:Conference or Workshop Item (Speech)
Title:Modeling and Simulation of a Spacecraft Payload Hardware Using Machine Learning Techniques
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Nepal, Ayush ManiAyush.Nepal (at) dlr.deUNSPECIFIED
Prat i Sala, ArnauArnau.PratiSala (at) dlr.deUNSPECIFIED
Höflinger, Kilian JohannKilian.Hoeflinger (at) dlr.dehttps://orcid.org/0000-0002-7565-8232
Gerndt, AndreasAndreas.Gerndt (at) dlr.dehttps://orcid.org/0000-0002-0409-8573
Lüdtke, DanielDaniel.Luedtke (at) dlr.dehttps://orcid.org/0000-0002-6758-1562
Date:2 November 2020
Journal or Publication Title:ASCEND
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
DOI :10.2514/6.2020-4219
ISBN:978-1-62410-608-8
Status:Published
Keywords:modeling and simulation, machine learning, neural networks, LSTM, artificial intelligence (AI), data-driven, physical system modeling
Event Title:ASCEND 2020
Event Location:Online
Event Type:international Conference
Event Dates:16-18 Nov 2020
Organizer:AIAA
HGF - Research field:other
HGF - Program:other
HGF - Program Themes:other
DLR - Research area:no assignment
DLR - Program:no assignment
DLR - Research theme (Project):no assignment, R - Vorhaben SISTEC (old)
Location: Braunschweig
Institutes and Institutions:Institute for Software Technology > Software for Space Systems and Interactive Visualisation
Institute for Software Technology
Deposited By: Nepal, Ayush Mani
Deposited On:16 Dec 2020 11:33
Last Modified:16 Dec 2020 11:33

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