Optimization of Chang'e-3 landing preparative orbit perilune based on improved genetic algorithm

Xianggen Liu, Huasong Zhong, Y. Meng, Sheng Chang
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Abstract

In this paper, improved genetic algorithm (GA) is used to search Chang'e-3 optimal landing preparative orbit perilune. Chang'e-3 lander as an object, the initial and final state of the lander and the kinetic equations in the lunar gravitational field are determined by reversely reasoning from the predetermined landing site in the main reduction stage. The lander motion state is non-linear and continuous, so this method takes advantage of genetic algorithms and discretized track to achieve the optimal location of perilune, with the help of Kepler's third law and the law of inertia. Simulation results show that the improved genetic algorithm has the better performance in convergence speed and can be applied to search for the global optimal location of perilune.
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基于改进遗传算法的嫦娥三号近地轨道着陆准备优化
本文采用改进的遗传算法(GA)搜索嫦娥三号最优着陆准备轨道。以嫦娥三号着陆器为对象,从主减速阶段的预定着陆点反向推理确定着陆器的初始状态和最终状态以及月球重力场下的动力学方程。由于着陆器的运动状态是非线性的、连续的,因此该方法利用遗传算法和离散轨迹,借助于开普勒第三定律和惯性定律来实现近月点的最优定位。仿真结果表明,改进的遗传算法在收敛速度上具有更好的性能,可用于搜索近日点的全局最优位置。
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