首页|Fast solution to the free return orbit's reachable domain of the manned lunar mission by deep neural network
Fast solution to the free return orbit's reachable domain of the manned lunar mission by deep neural network
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
万方数据
It is important to calculate the reachable domain(RD)of the manned lunar mission to evaluate whether a lunar landing site could be reached by the spacecraft.In this paper,the RD of free return orbits is quickly evaluated and calculated via the clas-sification and regression neural networks.An efficient database-generation method is developed for obtaining eight types of free return orbits and then the RD is defined by the orbit's inclination and right ascension of ascending node(RAAN)at the perilune.A classify neural network and a regression network are trained respectively.The former is built for classifying the type of the RD,and the latter is built for calculating the inclination and RAAN of the RD.The simulation results show that two neural networks are well trained.The classification model has an accu-racy of more than 99%and the mean square error of the regres-sion model is less than 0.01° on the test set.Moreover,a serial strategy is proposed to combine the two surrogate models and a recognition tool is built to evaluate whether a lunar site could be reached.The proposed deep learning method shows the superio-rity in computation efficiency compared with the traditional dou-ble two-body model.
NETL
NSTL
万方数据
