基于Kriging模型的QPSO算法在固体运载火箭弹道优化中的应用  

Application of Kriging Model Based Quantum Particle Swarms Optimizations Algorithm to Trajectory Optimization for Solid Launch Vehicle

作　　者：李靖[1] 廖瑛[1,2] 杨雅君[2] 

机构地区：[1]湘潭大学信息工程学院,湖南湘潭411105 [2]国防科学技术大学航天科学与工程学院,长沙410073

出　　处：《弹箭与制导学报》2014年第3期141-145,共5页Journal of Projectiles,Rockets,Missiles and Guidance

基　　金：航天支撑技术基金(2012-HT-GFKD)资助

摘　　要：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38.46 kg,三级一次工作时间减少了27 s。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 traj- ectory 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.

关 键 词：KRIGING QPSO 运载火箭 弹道优化 

分 类 号：TJ013[兵器科学与技术—兵器发射理论与技术]