Distributed Multi-Objective Optimization Control Strategy and Real-Time Assessment of Uncertainty Risks in Aerospace Science and Technology

DOI

10.2991/978-94-6463-676-5_35How to use a DOI?

Keywords

Distributed Optimization; Spacecraft Operations; Space Experiments; Risk Analysis; Real-Time Assessment

Abstract

The evolutionary structures of aerospace systems require a higher level of control strategies and the real-time assessment of possible risks for the successful implementation of designs and experiments in space conditions. This paper focuses on the Integrated Assessment and Control, Incorporated on the DMOCS architecture and the quantification of real-time uncertainty risk, in light of the International Space Station (ISS). The research investigates two primary objectives: first, the usefulness of DMOCS in establishing the optimal resource distribution to improve the functionality of distributed systems in spacecraft control, and second, the result of applying real-time uncertainty risk assessment techniques to increase the efficiency of space experimentations. A qualitative research approach was employed, and the data were gathered from scholarly journals, and official documents only. The thematic synthesis was conducted with a view of discovering different themes regarding optimization and risk assessment. Recommendations are made for the application of these strategies in long and high-risk space missions, and ideas are presented for future research in the areas of hybrid optimization and handling uncertainty.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Boya Jia
AU  - Yixiao Wang
AU  - Maosen Fan
PY  - 2025
DA  - 2025/04/15
TI  - Distributed Multi-Objective Optimization Control Strategy and Real-Time Assessment of Uncertainty Risks in Aerospace Science and Technology
BT  - Proceedings of the 2024 6th Management Science Informatization and Economic Innovation Development Conference (MSIEID 2024)
PB  - Atlantis Press
SP  - 362
EP  - 376
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-676-5_35
DO  - 10.2991/978-94-6463-676-5_35
ID  - Jia2025
ER  -