Issue |
E3S Web Conf.
Volume 477, 2024
International Conference on Smart Technologies and Applied Research (STAR'2023)
|
|
---|---|---|
Article Number | 00022 | |
Number of page(s) | 10 | |
DOI | https://doi.org/10.1051/e3sconf/202447700022 | |
Published online | 16 January 2024 |
Guidance and Control Systems for Multi-Satellite Assembly using Decentralized Nonlinear Model Predictive Control
Department of Mechanical and Aerospace Engineering, Collage of Engineering, United Arab Emirates University, Alain P. O. Box15551, United Arab Emirates
* Corresponding author: at uaeu@ac.ae
Assembly of multiple satellites enables to replace the functionality of one large satellite by multiple smaller satellites for many applications and missions such as formation flying, multi robot planetary exploration, and satellites warms. In this paper, a novel decentralized guidance and control (G&C) algorithms is developed for multi-satellite assembly in proximity operations based on Non linear Model Predictive Control (NMPC).The two-body relative motion model is utilized in designing the G&C systems. Decentralization avoids the single point of failure (i.e., the leader satellite), which enhances the robustness of the system. The NMPC is utilized because of itsability to handle the output and the input constraints. Collision avoidance is ensured by defining a quadratic constraint equation. Moreover, the optimal thrust vector is computed while considering the control input saturation. The mission is to assemblemultiple satellites into a cubic configuration, where each satellite approaches a cube vertex. Totes the algorithms’ effectiveness and to increase the level of confidence prior flight, the proposed closed-loop G&C system is demonstrated by using MATLAB andtested for a relative motion model with J2 perturbation. The simulation results showsmooth conversion of all satellites to the target while satisfying the input and outputconstraints.
Key words: GNC / Multi-Satellite Assembly / Spacecraft Relative Motion / Decentralized Control / Nonlinear MPC
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.