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将太阳系多目标探测的轨道优化设计问题转换成非线性规划问题,建立了轨道优化模型。针对非线性规划问题解的多峰性,设计了一种融合改进的网格搜索算法和差分进化算法的组合优化算法。利用改进的网格搜索算法以适当的步长寻找理想的发射窗口和各阶段转移时间,产生差分进化的初始群体,进而使用差分进化算法搜索初始群体附近的子空间,通过全局范围内的比较得到较理想的结果。最后以2018～2020年太阳系多目标探测为例,面向土星环绕探测任务完成了飞行中途探测太阳系多颗大行星的轨道优化设计。数值仿真结果表明上述算法对太阳系多目标探测轨道优化设计具有较好的通用性和应用参考价值。
The orbit optimization design problem of multi-target detection of the solar system is transformed into a nonlinear programming problem, and an orbit optimization model is established. Aiming at the multi-peaks of solutions to nonlinear programming problems, a combinational optimization algorithm based on improved grid search algorithm and differential evolution algorithm is designed. The improved grid search algorithm is used to find the ideal launch window and the transfer time of each stage in proper steps to generate the initial population of differential evolution. Then the differential evolution algorithm is used to search the subspace near the initial population, and the global comparison is obtained The ideal result. Finally, taking the multi-target detection of the solar system from 2018 to 2020 as an example, the orbital optimization of multi-planets in the solar system during mid-flight is completed for the Surrounding Surveying Mission. The numerical simulation results show that the above algorithm has good versatility and application reference value for the optimization design of multi-target orbital detection system in the solar system.