随机权重粒子群算法优化磁轴承系统  

Optimization of Magnetic Bearing System Based on Random Weight Particle Swarm Algorithm

作　　者：张建生[1,2] 王一夫[1] 马啸宇[1] 吴璇[1] 

机构地区：[1]南通大学电气工程学院,江苏南通226019 [2]常州工学院电气与光电工程学院,江苏常州213002

出　　处：《轴承》2017年第10期10-14,共5页Bearing

基　　金：国家自然科学基金项目(51175052)

摘　　要：为了提高单自由度主动磁悬浮轴承系统的稳定性,采用随机权重粒子群算法与传统PID控制相结合的方法,将随机权重粒子群算法与线性递减权重粒子群算法进行函数测试对比,结果表明,随机权重粒子群算法能够更快、更准确地找出优化函数的最优值。通过MATLAB/Simulink构建系统模型并进行仿真对比,证明随机权重粒子群算法可以更好地提高系统的稳定性。In order to improve stability of active magnetic bearing system with single degree of freedom,a random weight particle swarm algorithm is combined with traditional PID control.The random weight particle swarm algorithm and linear decreasing weight particle swarm algorithm are compared by function test.The results show that the random weight particle swarm algorithm is able to find out optimal value of optimization function faster and more accurately.The system model is constructed by MATLAB/Simulink,and the simulation comparison is carried out,it is proved that the random weight particle swarm algorithm is able to improve stability of system better.

关 键 词：主动磁悬浮轴承 PID控制 随机权重粒子群算法 MATLAB 

分 类 号：TH133.31[机械工程—机械制造及自动化] TP273[自动化与计算机技术—检测技术与自动化装置]