Optimization of lunar soft landing trajectory based on ant colony algorithm

被引：0
|
作者：
Duan, Jia-Jia [1 ]
Xu, Shi-Jie [1 ]
Zhu, Jian-Feng [2 ]
机构：
[1] School of Astronautics, Beijing University of Aeronautics and Astronautics, Beijing 100083, China
[2] Center for Space Science and Applied Research, China Academy of Sciences, Beijing 100080, China
来源：
Yuhang Xuebao/Journal of Astronautics | 2008年 / 29卷 / 02期
关键词：
Local search (optimization) - Problem solving - Ant colony optimization - Lunar landing - Aerodynamics - Landing - Moon;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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 optimum trajectory, which has a fuel consumption quite close to the result of Pontryagin's maximum principle. It is also proved DACA has a strong ability in both global search and local search.
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页码：476 / 481
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