摘要
为解决多在轨服务飞行器的目标分配问题,为提高服务效率和减少燃料消耗,对多在轨服务飞行器目标分配的模型和方法进行了研究。首先对在轨服务任务的当前态势进行了分析,以服务效能、燃料消耗、燃料消耗均衡性为指标,建立了多在轨服务飞行器目标分配模型,其次对标准粒子群算法的粒子和位置的更新策略及惯性权重和学习因子进行了改进,并引入禁忌搜索算法,提出了基于禁忌离散粒子群算法的模型求解方法。仿真结果表明,改进的算法能快速的确定出合理的目标分配方案。
In order to solve the problem of target allocation for multiple on-orbit service vehicles, we studied the target allocation model and its method. First, the current situation of on-orbit service mission was analyzed, based on the analysis of key factors including service efficiency, fuel consumption and fuel consumption, and the target alloca- tion model for multi on-orbit service vehicles was formulated. Second, the update strategy of particle and position of standard particle swarm optimization as well as the inertia weight and learning factors were improved, on this basis, the method based on tabu discrete particle swarm optimization algorithm was presented. The simulation results show that the proposed TS-DPSO algorithm can solve the target allocation problem for multiple on-orbit service vehicles effectively.
出处
《计算机仿真》
北大核心
2017年第1期90-93,128,共5页
Computer Simulation
关键词
在轨服务飞行器
目标分配
服务效能
禁忌离散粒子群算法
On-orbit service vehicle （ OSV ）
Target allocation （TA）
Service efficiency
Tabu discrete particle swarm optimization（TS-DPSO）
