弹道学报2016，Vol.28Issue(1)：33-38,44,7.
基于遗传粒子群算法的底排参数优化
Optimization on Base Bleed Parameters Based on Genetic Particle Swarm Algorithm
摘要
Abstract
To optimize the structure of base bleed device and the burning rate coefficient of grain,a certain type of base bleed projectile was taken as instance, and the design variables and target function were analyzed and established. Considering both advantages of genetic algorithm and particle swarm optimization,a genetic algorithm-particle swarm optimization( GA-PSO) algorithm was designed. Combined with the model of base bleed interior and exterior ballistics,a model of base bleed parameters optimization was established based on GA-PSO. Results show that the optimization scheme can increase the drag-reduce rate,extend base bleed work time for 9. 56 s and increase remaining velocity of 6. 01 m/s,and the maximum range increases by 1 892 . 95 m ( 5 . 02%) . The designed GA-PSO is stable and has a fast convergence speed. The optimization model offers reference for the design of base bleed device,and the model can be a basic model for other similar optimization problems.关键词
底部排气弹/增程/参数优化/遗传粒子群算法Key words
base bleed projectile/extended range/parameter optimization/GA-PSO分类
军事科技引用本文复制引用
谢利平,史金光,李元生,邱海迪,黄玉才..基于遗传粒子群算法的底排参数优化[J].弹道学报,2016,28(1):33-38,44,7.基金项目
中国博士后科学基金项目(2013M541676) （2013M541676）
