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Sequential convex programming method using adaptive mesh refinement for entry trajectory planning problem
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DOI：10.1016/j.ast.2020.106374.png)
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Abstract
En 中文
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. (C) 2020 Elsevier Masson SAS. All rights reserved.
Keywords:
Adaptive mesh refinement
Sequential convex programming
Convergence condition
Entry trajectory planning
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