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Multi-objective optimization of parachute triggering algorithm for Mars exploration

机译:火星勘探降落伞触发算法的多目标优化

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摘要

A multi-objective optimization procedure to design parachute triggering algorithm, based on Monte Carlo analysis of flight uncertainties, has been developed in this paper. Most of Mars explorations missions utilize parachute for a safe descent through the lowest of the atmosphere. The parachute triggering algorithm is designed to accommodate the range of off-nominal entry trajectories, and is aimed to parachute opening in certain range of Mach numbers, dynamic pressure and altitude. Our novel algorithm takes the fight uncertainty into the account through Monte Carlo analysis, selects maximization of altitude statistical mean and minimization of Mach number statistical mean as two objectives, then employs multi-objective evolutionary algorithm based on decomposition (MOEA/D), to search the Pareto-front framework. Such a methodology can be implemented on the future design of entry, descent, and landing (EDL) mission.
机译:本文开发了一种基于蒙特卡罗分析的蒙特卡罗分析来设计降落伞触发算法的多目标优化过程。大多数火星探索任务利用降落伞通过最低的大气来安全下降。降落伞触发算法旨在适应非名义入口轨迹的范围,并旨在降落在一定范围的马赫数,动态压力和高度范围内的降落伞开口。我们的小说算法通过Monte Carlo分析将不确定性的战斗不确定性,选择最大化的高度统计均值和Mach数量统计均值的最小化作为两个目标,然后采用基于分解(MOEA / D)的多目标进化算法,进行搜索帕累托 - 前框架。这种方法可以在未来的进入,下降和着陆(EDL)任务的设计上实施。

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