基于遗传粒子群算法的底排参数优化

为优化底排装置结构和药柱燃速系数,以某型底部排气弹为例,分析确立了设计变量和目标函数,综合遗传算法和粒子群优化的优点,设计了遗传粒子群优化算法,结合建立的底排内外弹道模型,构建了基于GA-PSO的底排参数优化模型。算例中优化方案能增加底排弹的减阻率,底排工作时间延长9.56 s,落点存速增加6.01 m/s,最大射程增加1 892.95 m,增幅5.02%。该文设计的GA-PSO具有较好的稳定性和较快的收敛速度,优化模型可以为底部排气弹底排装置的设计提供参考,也可以作为其他相似寻优问题的基本模型。

Optimization on Base Bleed Parameters Based on Genetic Particle Swarm Algorithm

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.