基于蚁群算法的月球软着陆轨迹优化  

Optimization of Lunar Soft Landing Trajectory Based on Ant Colony Algorithm

作　　者：段佳佳[1] 徐世杰[1] 朱建丰 

机构地区：[1]北京航空航天大学宇航学院,北京100083 [2]中国科学院空间科学与应用中心,北京100080

出　　处：《宇航学报》2008年第2期476-481,488,共7页Journal of Astronautics

基　　金：国家自然科学基金(10702003)

摘　　要：针对基于最省燃料的月球软着陆轨迹优化问题进行了研究。首先通过改进的函数逼近法,将月球软着陆的轨迹优化问题转化为参数优化问题,并且使优化变量及状态变量均有明确的物理意义。然后利用增加了局部搜索策略的十进制蚁群算法对该优化问题进行研究。仿真算例证明十进制蚁群算法能快速地搜索到满足终端约束条件的最优月球软着陆轨迹,而且燃料消耗也与采用极大值原理得到的最优燃料消耗相当;同时与改进的遗传算法-自适应模拟退火遗传算法相比,在优化精度相差不多的情况下十进制蚁群算法收敛速度要快很多。仿真结果也说明增加局部搜索策略的十进制蚁群算法具有优良的全局和局部搜索能力。The optimization of lunar soft landing trajectory was studied in this paper.Firstly a new parameterized method was developed to convert the trajectory optimization problem into a parameter optimization problem,in which all optimization parameters and motion states had specific physical meanings.Then a new decimalization ant colony algorithm(DACA) with a local search strategy was proposed and applied to solve this optimization problem.Simulation results show that DACA is efficient for finding the global opti...

关 键 词：轨迹优化 月球软着陆 蚁群算法 局部搜索策略 

分 类 号：V448.233[航空宇航科学与技术—飞行器设计]