Sequential convex programming method using adaptive mesh refinement for entry trajectory planning problem

Sequential convex programming method is one of the potential approaches to make trajectory generation onboard. However, the contradiction between the solution accuracy and the computational efficiency restricts its application. To overcome the difficulty, a novel sequential convex programming method...

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Vydáno v:Aerospace science and technology Ročník 109; s. 106374
Hlavní autoři: Zhou, Xiang, He, Rui-Zhi, Zhang, Hong-Bo, Tang, Guo-Jian, Bao, Wei-Min
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Masson SAS 01.02.2021
Témata:
Adaptive mesh refinement
Convergence condition
Entry trajectory planning
Sequential convex programming
Sequential convex programming
Adaptive mesh refinement
Convergence condition
Entry trajectory planning
ISSN:1270-9638, 1626-3219
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Shrnutí:Sequential convex programming method is one of the potential approaches to make trajectory generation onboard. However, the contradiction between the solution accuracy and the computational efficiency restricts its application. To overcome the difficulty, a novel sequential convex programming method based on customized adaptive mesh refinement is proposed in this paper. The main contribution includes two aspects. Firstly, a customized adaptive mesh refinement method is developed. The mesh points are adjusted adaptively based on the linearization error after each iteration, and thus the number of mesh points is changed. Secondly, an unconventional convergence condition is proposed, which can make the sequential convex programming method converges to a feasible solution of the original problem with fewer iterations. Taking the entry trajectory planning problem as an example, the simulation results show that the proposed method can decrease the number of mesh points while ensuring the feasibility of converged solution. Due to the fewer iterations, the computational time to solve the original problem is decreased. As a result, a good balance between solution accuracy and computational efficiency is achieved.
ISSN:1270-9638
1626-3219
DOI:10.1016/j.ast.2020.106374