论文部分内容阅读
针对多GEO卫星接近观测任务,研究了时间约束下能量消耗最优的多任务规划问题。按照上层面向任务顺序安排,下层面向时间分配,建立了一对多任务模式下的二层非线性规划模型。基于双脉冲多圈Lambert交会原理,将下层连续变量时间分配问题转化为0-1整数规划模型,并设计了遗传-分枝定界算法来求解二层规划模型。仿真结果表明,通过合理安排任务顺序和分配时间,可以大大降低观测航天器的机动能量消耗;观测任务时间和目标航天器之间的相位关系是影响规划结果的两个主要因素。
Aiming at the multi-GEO satellite observing mission, the multi-task scheduling problem with the best energy consumption under time constraint is studied. According to the arrangement of tasks in the upper level and the lower level in time, a two-level nonlinear programming model in one-to-many task mode is established. Based on the principle of double-pulse multi-turn Lambert rendezvous, the problem of time distribution of lower continuous variables is transformed into 0-1 integer programming model, and genetic-branch-and-bound algorithm is designed to solve the two-level programming model. The simulation results show that maneuvering energy consumption of the spacecraft can be greatly reduced by reasonably arranging the order of tasks and allocating time. The phase relationship between the mission time and the target spacecraft is the two main factors that affect the planning results.