应用基于Kriging模型的量子粒子群优化算法研究了固体运载火箭弹道优化问题。该方法利用Kriging方法建立弹道计算近似模型,再引入量子粒子群算法建立了基于代理模型的优化框架。仿真结果表明,此方法可有效完成弹道参数寻优,箭体运载能力提高了38.46kg,三级一次工作时间减少了27s。此算法参数设置少,易于实现,能提高运载火箭综合性能,具有一定的工程应用价值。

Trajectory optimization of solid launch vehicle was studied using Kriging model based quantum particle swarms optimization. The method uses Kriging method to establish trajectory calculation approximate model, and the optimization framework based on surrogate model was established by inducing quantum particle swarm optimization. The simulation results show that the method can effectively optimize trajectory parameters, the launching capacity of the launch vehicle is increased by 38 kg and work time on first time of third stage is reduced by 27s. The method is featured with less parameter set, can be easily realized and improve overall performance of the launch vehicle. All of those demonstrate that the research has certain engineering application value.