改进粒子群优化算法在亚轨道飞行器固液混合发动机设计中的应用

池元成; 朱浩; 方杰; 蔡国飙

改进粒子群优化算法在亚轨道飞行器固液混合发动机设计中的应用

北京航空航天大学宇航学院,北京 100191

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出版历程
- 收稿日期: 2010-09-15
- 修回日期: 2010-12-28
- 刊出日期: 2011-09-28

Optimal design of hybrid rocket motor for sub-orbital vehicle based on improved particle swarm optimization

School of Astronautics, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

摘要

摘要: 针对粒子群优化算法在求解多维复杂优化问题时容易陷入局部最优的缺点,提出了动态目标粒子群优化算法,通过分析寻优过程中粒子与个体最优位置和全局最优位置之间存在的位置关系,建立了新的速度更新公式.最后,应用该算法对某型号亚轨道飞行器固液混合发动机进行了优化设计.仿真结果表明,改进算法搜索能力强、收敛速度快,能有效解决此类问题,可为亚轨道飞行器的发动机优化设计提供理论参考.
- 粒子群优化 /
- 动态目标 /
- 固液混合发动机 /
- 亚轨道飞行器 /
- 优化设计
Abstract: An improved particle swarm optimization(PSO),called as dynamic target particle swarm optimization (DTPSO),was proposed to use dynamic target strategy for solving complex multi-dimensional optimization problems by analyzing the position between individual particles,personal best and global best.As a specific example,the DTPSO was applied to the optimal design for hybrid rocket for a certain hybrid rocket motor of sub-orbital vehicle.The optimization results show that algorithm has strong search capability,and can also reach convergence rapidly and solve such problem effectively.All those can provide a theoretical reference for the research of sub-orbital vehicle engine's optimal design.
- particle swarm optimization /
- dynamic target /
- hybrid rocket motor /
- sub-orbital vehicle /
- optimal design

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参考文献(12)

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