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针对太阳系中全部的248997颗行星的探测问题,给出了一种关于探测飞行器的深空探测全局四维轨迹(t,x,y,z)优化方案,即飞行器从地球发射进入太阳系并采用小推力控制,优化方案的性能指标为飞行器与太阳系中全部行星中相遇和交会的星的数量最多并且燃料消耗最少。本方案给出了四维飞行轨迹进行全局优化的一套算法,该算法由搜索算法和四维轨迹优化算法组成。此搜索算法从太阳系的248997颗行星中寻找获得尽可能多的经过近地球3维走廊内的行星;而四维轨迹优化算法由改进的动态规划算法、基于最优控制理论的共轭梯度算法和静态参数优化算法组成,其中静态参数优化算法用于搜索最优发射时间窗口。基于该组合算法,通过长时间的大规模的飞行数字仿真,最终计算出探测器的四维最优飞行轨迹,在一年内路过了太阳系中全部行星中的12颗行星。
Aiming at the detection of all 248997 planets in the solar system, an optimization scheme of the global 4D trajectory (t, x, y, z) of deep space exploration of the detection vehicle is given. That is, the launch of the aircraft from the Earth into the solar system and the use of small thrust Control, optimization program performance indicators for the aircraft and the solar system in all the planets meet and meet the largest number of stars and fuel consumption at least. This program gives a set of algorithms for global optimization of four-dimensional flight path. The algorithm consists of search algorithm and four-dimensional trajectory optimization algorithm. This search algorithm seeks to obtain as many planets in the 3-D corridor through the Earth as possible from 248,997 planets in the solar system. The 4-D trajectory optimization algorithm consists of an improved dynamic programming algorithm, a conjugate gradient algorithm based on the optimal control theory and a static Parameter optimization algorithm, in which the static parameter optimization algorithm is used to search the optimal transmission time window. Based on the combined algorithm, the four-dimensional optimal trajectory of the detector is finally calculated through long-term and large-scale flight digital simulation, passing 12 planets of all the planets in the solar system within a year.