Neural Power-Optimal Magnetorquer Solution for Multi-Agent Formation and Attitude Control
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arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866911659419762688 |
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| author | Takahashi, Yuta Sakai, Shin-ichiro |
| author_facet | Takahashi, Yuta Sakai, Shin-ichiro |
| contents | This paper presents a learning-based current calculation model to achieve power-optimal magnetic-field interaction for multi-agent formation and attitude control. In aerospace engineering, electromagnetic coils are referred to as magnetorquer (MTQ) coils and used as satellite attitude actuators in Earth's orbit and for long-term formation and attitude control. This study derives a unique, continuous, and power-optimal current solution via sequential convex programming and approximates it using a multilayer perceptron model. The effectiveness of our strategy was demonstrated through numerical simulations and experimental trials on the formation and attitude control. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_00548 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Neural Power-Optimal Magnetorquer Solution for Multi-Agent Formation and Attitude Control Takahashi, Yuta Sakai, Shin-ichiro Multiagent Systems This paper presents a learning-based current calculation model to achieve power-optimal magnetic-field interaction for multi-agent formation and attitude control. In aerospace engineering, electromagnetic coils are referred to as magnetorquer (MTQ) coils and used as satellite attitude actuators in Earth's orbit and for long-term formation and attitude control. This study derives a unique, continuous, and power-optimal current solution via sequential convex programming and approximates it using a multilayer perceptron model. The effectiveness of our strategy was demonstrated through numerical simulations and experimental trials on the formation and attitude control. |
| title | Neural Power-Optimal Magnetorquer Solution for Multi-Agent Formation and Attitude Control |
| topic | Multiagent Systems |
| url | https://arxiv.org/abs/2412.00548 |