摘要
将混沌搜索引入到粒子群优化方法中,并将改进的算法应用在三轴气浮台平台优化设计中。该算法既保持了粒子群算法结构简单、快速收敛的特点,又利用了混沌算法易于逃离局部极小值的特点。测试及应用结果表明该方法改善了算法的全局搜优性能,提高了算法的收敛速度和计算精度。
A particle swarm optimization (PSO) based on chaos searching was introduced to optimize the platform of tri-axial airbearing satellite attitude motion simulator. The improved PSO algorithm has the advantage of simplification for implement of original particle swarm optimization, and the advantage of fast convergence, easy to escape local minima for chaos optimization algorithm. The results of experiment show the proposed approach has better global search capability and fast convergence and high computation precision.
出处
《机床与液压》
北大核心
2008年第5期28-30,67,共4页
Machine Tool & Hydraulics
基金
沈阳工业大学博士启动基金(521101302)
关键词
三轴气浮台
粒子群
混沌
优化
Tri-axial air-bearing simulator
PSO algorithm
Chaos
Optimization