Solar-Sail Deep Space Trajectory Optimization Using Successive Convex Programming
Fuente:
arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2019
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866917874322374656 |
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| author | Song, Yu Gong, Shengping |
| author_facet | Song, Yu Gong, Shengping |
| contents | This paper presents a novel methodology for solving the time-optimal trajectory optimization problem for interplanetary solar-sail missions using successive convex programming. Based on the non-convex problem, different convexification technologies, such as change of variables, successive linearization, trust regions and virtual control, are discussed to convert the original problem into the formulation of successive convex programming. Because of the free final-time, successive linearization is performed iteratively for the nonconvex terminal state constraints. After the convexification process, each of problems becomes a convex problem, which can be solved effectively. An augmented objective function is introduced to ensure the convergence performance and effectiveness of our algorithm. After that, algorithms are designed to solve the discrete sub-problems in a successive solution procedure. Finally, numerical results demonstrate the effectiveness and accuracy of our algorithms. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_1901_02145 |
| institution | arXiv |
| publishDate | 2019 |
| record_format | arxiv |
| spellingShingle | Solar-Sail Deep Space Trajectory Optimization Using Successive Convex Programming Song, Yu Gong, Shengping Computational Engineering, Finance, and Science Systems and Control This paper presents a novel methodology for solving the time-optimal trajectory optimization problem for interplanetary solar-sail missions using successive convex programming. Based on the non-convex problem, different convexification technologies, such as change of variables, successive linearization, trust regions and virtual control, are discussed to convert the original problem into the formulation of successive convex programming. Because of the free final-time, successive linearization is performed iteratively for the nonconvex terminal state constraints. After the convexification process, each of problems becomes a convex problem, which can be solved effectively. An augmented objective function is introduced to ensure the convergence performance and effectiveness of our algorithm. After that, algorithms are designed to solve the discrete sub-problems in a successive solution procedure. Finally, numerical results demonstrate the effectiveness and accuracy of our algorithms. |
| title | Solar-Sail Deep Space Trajectory Optimization Using Successive Convex Programming |
| topic | Computational Engineering, Finance, and Science Systems and Control |
| url | https://arxiv.org/abs/1901.02145 |