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Pérez-Muñoz, ángel-GroverCorresponding AuthorAlonso, AlejandroAuthorPorras-Hermoso, AngelAuthorPerez, Maria SAuthor

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August 14, 2025
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Feasibility of Deep Reinforcement Learning for the real-time attitude control of a satellite system

Publicated to: JOURNAL OF SYSTEMS ARCHITECTURE. 167 103513- - 2025-10-01 167(), DOI: 10.1016/j.sysarc.2025.103513

Authors:

Perez-Munoz, Angel-Grover; Lopez-Garcia, Guillermo; Garcia-Villoria, Irene; Alonso, Alejandro; Porras-Hermoso, Angel; Perez, Maria S
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Affiliations

Univ Politecn Madrid, Informat Proc & Telecommun Ctr, Ave Complutense 30, 28040 Madrid, Spain - Author
Univ Politecn Madrid, Inst Univ Microgravedad Ignacio Riva, Plaza Cardenal Cisneros 3, Madrid 28040, Spain - Author
Univ Politecn Madrid, Ontol Engn Grp, ETS Ingn Informat, Campus Montegancedo, Madrid 28660, Spain - Author
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Abstract

Although Machine Learning (ML) is widely used in a variety of interdisciplinary applications, its implementation in safety-critical systems, such as the Attitude Control System (ACS) of a satellite, poses numerous challenges. While previous studies have shown promising results, there is a lack of information on the design and development process for the application of ML in real-time control systems. This paper presents the implementation of a Deep Reinforcement Learning (DRL) model for a magnetic-based ACS of the UPMSat-2 satellite. The primary objective is not only to design, implement, and validate an RL agent, but also to provide some insights and criteria of the decision-making process to achieve an adequate model. The system was trained and validated on a simulation model with positive results. To further validate non-functional requirements, the resulting trained agent was tested on a real-time embedded system according to safety standards. The obtained quantitative metrics and performance results show the ability of the agent to maintain the satellite's attitude across various operational phases, leveraging its adaptability to dynamic conditions.
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Keywords

Artificial intelligenceEmbedded systemEmbedded systemsNeural network controllersSafety-critical systems

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal JOURNAL OF SYSTEMS ARCHITECTURE due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2025, it was in position 23/129, thus managing to position itself as a Q1 (Primer Cuartil), in the category Computer Science, Software Engineering.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-26:

  • WoS: 1
  • Scopus: 1
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-26:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 8 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

    It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

    • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/90311/

    As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

    • Views: 181
    • Downloads: 307
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    Leadership analysis of institutional authors

    There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (PEREZ MUÑOZ, ANGEL GROVE) and Last Author (PEREZ HERNANDEZ, MARIA DE LOS SANTOS).

    the author responsible for correspondence tasks has been PEREZ MUÑOZ, ANGEL GROVE.

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    Awards linked to the item

    This work was mainly developed under the project OAPES-CM "Operacion Avanzada de Pequenos Satelites" (Ref.: Y2020/NMT-6427) and PRESECREL (PID2021-124502OB-C43) . The authors also acknowledge the financial support of the Ministerio de Ciencia e Innovacion, Spain, and the Comunidad de Madrid Proyectos Sinergicos from the I+D plan (Spain) , as well as the collaboration with the partners in these projects.
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