摘要
为了解决燃料最省和时间-燃料组合最优的航天器轨道交会问题,采用遗传算法对最优多脉冲交会轨迹进行设计.把最优脉冲的幅值、方向和真近点角作为编码变量,根据最优交会问题的终端边界条件和必要条件来设计适应度函数.该方法分别用于最优双脉冲交会、具有初始滑行段的最优双脉冲交会、最优三脉冲交会和时间-燃料组合最优三脉冲交会四个仿真实例.将仿真结果与牛顿法求解的精确最优解比较,可以看出用遗传算法求解的最优解具有较高精度,证明了该方法的合理性和有效性.
The optimal multiple-impulsive rendezvous trajectories were designed using genetic algorithms to solve the rendezvous problem of minimum fuel and time-fuel combinatorial optimization. The magnitudes, directions and burn times of the optimal impulses were coded into genetic algorithms, and the fitness functions were designed to evaluate the final states and necessary conditions. The method was used for four test cases, including the two-impulse rendezvous, the optimal two-impulse rendezvous with initial coastings, the optimal three-impulse rendezvous and time-fuel combinatorial optimal three-impulse rendezvous. Compared with the precision optimal solutions solved by Newton iterative algorithm, the GA solutions are more precise, thus the method in the paper is proved to be correct and effective.
出处
《哈尔滨工业大学学报》
EI
CAS
CSCD
北大核心
2008年第9期1345-1348,共4页
Journal of Harbin Institute of Technology
关键词
轨迹优化
多脉冲交会
遗传算法
主矢量理论
trajectory optimization
multiple-impulse rendezvous
genetic algorithms
primer-vector theory.
