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首页> 外文期刊>Transactions of the Japan society for aeronautical and space sciences >Ascent Phase Trajectory Optimization for Vehicle with Restricted Space
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Ascent Phase Trajectory Optimization for Vehicle with Restricted Space

机译：受限空间车辆的上升相轨迹优化

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摘要

For flight safety, space is often restricted while the vehicle climbs to the target. A general two-dimensional (2-D) vehicle model is unsuitable for ascent when space is restricted because it considers only longitudinal degrees of freedom. Requiring into ascent in three-dimensional (3-D) scenarios as well as into relationships between the 2-D and 3-D trajectories. This paper reports 2-D and 3-D ascent phase minimum time-to-climb and minimum fuel-to-climb problems in different restricted spaces. The Gauss Pseudospectral Method (GPM) is used to transform the trajectory optimization problem into a Nonlinear Program (NLP) problem that can be solved by SNOPT based on a correct initial guess. The results in different restricted spaces illustrate the effect on 2-D and 3-D flight trajectories. Numerical evidence of optimality to trajectories is verified by estimating co-state information and the Hamiltonian.
机译：为了飞行安全，车辆爬升到目标位置时通常会限制空间。当空间受限时，一般的二维（2-D）车辆模型不适合上升，因为它仅考虑纵向自由度。要求在三维（3-D）场景中上升以及在2-D和3-D轨迹之间存在关系。本文报告了在不同限制空间内的2D和3D上升阶段最小爬升时间和最小燃料爬升问题。高斯伪谱方法（GPM）用于将轨迹优化问题转换为非线性程序（NLP）问题，该问题可以由SNOPT基于正确的初始猜测来解决。在不同的受限空间中的结果说明了对2-D和3-D飞行轨迹的影响。通过估计共态信息和哈密顿量，可以证明轨迹最优的数值证据。

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