摘要
由于航天器远距离变轨时各种误差和摄动的存在,要使其精确到达目标点,就必须在转移轨道的中途对其飞行轨迹进行修正。对传统的蚁群算法进行了改进使之适用于连续参数优化问题,并增加了算法的局部搜索策略以避免陷于局部最优,同时通过引进伪梯度信息,改进了算法的收敛速度。利用改进后的蚁群算法,针对修正次数和修正时间点均未定的中途修正问题进行优化,寻找到最优的修正次数和时间点,并根据不同的权重系数,制定相应的修正策略,以达到最终位置误差和修正所消耗的速度脉冲两者的综合最优。仿真结果显示,采用中途修正减少了航天器与目标点的最终位置误差,证明了蚁群算法对转移轨道中途修正问题的有效性。
During the long range orbital transfer, the spacecraft is incapable to arrive at the target point precisely due to various errors and perturbations. Therefore the midcourse correction is necessary. The traditional ant colony algorithm was improved to be applicable to the optimization of continuous parameters. And local search strategy was appended to the algorithm to avoid being immerged in the local optimization. Meanwhile the algorithm "s convergent speed was also improved by using pseudo-gradient information. The improved ant colony algorithm was adopted to search the optimal variables, which were times and time points of corrections. And according to the different weight coefficients, the correction strategy was proposed to achieve the synthesis optimization of final position error and velocity impulses. Simulation results validate that the midcourse corrections reduce the final position error between the spacecraft and target point. Consequently the effect of ant colony algorithm is verified.
出处
《系统仿真学报》
CAS
CSCD
北大核心
2009年第14期4400-4404,共5页
Journal of System Simulation
基金
国家自然科学基金(60535010)
关键词
中途修正
综合最优
蚁群算法
修正策略
midcourse correction
synthesis optimization
ant colony algorithm
correction strategy