Delta-V genetic optimisation of a trajectory from Earth to Saturn with fly-by in Mars

F. A. Zotes, M. Peñas
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引用次数: 5

Abstract

The aim of this article is to analyse the results obtained when using a genetic algorithm (GA) to optimise the interplanetary trajectory of a spacecraft. The desired trajectory should visit Saturn, after performing a gravitational assistance or fly-by in planet Mars. The GA tunes a set of variables, in order to achieve the mission purpose while satisfying the constraints and minimizing the delta-V of the mission. Due to the complexity of the implemented models and the lack of analytical solutions, an alternative non-traditional algorithm provided by soft-computing techniques such as GA is necessary to achieve an optimum solution. The positions of planets as provided by Jet Propulsion Laboratory have been considered. A variable mutation rate has been implemented that broadens the search area whenever the population becomes uniform. The results are very useful from the point of view of mission analysis and therefore can be used as an initial guess for further optimizations. They can also be the first step for a more refined analysis and time-consuming simulations based on more complex models of orbital perturbations.
Delta-V从地球到土星的轨迹遗传优化,飞越火星
本文的目的是分析使用遗传算法(GA)优化航天器行星际轨迹时获得的结果。在执行重力辅助或飞越火星之后,期望的轨道应该访问土星。遗传算法对一组变量进行调谐,以在满足约束条件的同时实现任务目的,并使任务的δ - v最小。由于实现模型的复杂性和缺乏解析解,需要由遗传算法等软计算技术提供的替代非传统算法来实现最优解。考虑了喷气推进实验室提供的行星位置。一个可变的突变率已经被实现,当种群变得均匀时,扩大了搜索区域。从任务分析的角度来看,结果非常有用,因此可以用作进一步优化的初步猜测。它们也可以成为基于更复杂的轨道扰动模型的更精细的分析和耗时的模拟的第一步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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