改进粒子群算法在主动磁悬浮轴承系统中的应用  

Improved particle swarm optimization in active magnetic bearing system

作　　者：张建生[1] 王一夫[1] 马啸宇[1] 沈莹雅 

机构地区：[1]南通大学电气工程学院,江苏南通226019

出　　处：《制造技术与机床》2016年第9期45-49,共5页Manufacturing Technology & Machine Tool

基　　金：国家自然科学基金项目(51175052)

摘　　要：通过分析得知,主动磁悬浮轴承系统本身是一个不稳定系统,可以采用PID控制器对其进行控制。但是传统PID控制在主动磁悬浮轴承系统中还存在着不足之处,为此可以将粒子群优化算法与常规PID控制相结合,对PID控制器中的参数进行优化,使系统能够达到更好的控制效果。采用了一种改进粒子群算法,对算法中的惯性权重w进行自适应调节,从而使得算法能够更快、更准确地寻找到最优值。通过Matlab/Simulink构建系统模型并进行仿真对比,改进粒子群算法可以使得系统达到更好的控制效果。The analysis shows that the active magnetic bearing system is an unstable system,we can use a PID controller to control it.However,the traditional PID control still has some shortcomings in active magnetic bearing system,we can optimize the PID controller parameters through combining particle swarm optimization algorithm with conventional PID control,and make the system achieve better control effect.This article uses an improved particle swarm algorithm and adjusts its inertia weight w adaptive,so that the algorithm can find the optimal value more quickly and accurately.Through constructing system model by Matlab/Simulink and simulation comparison,improved particle swarm algorithm enables the system to achieve better control effect.

关 键 词：主动磁悬浮轴承 改进粒子群算法 PID控制 MATLAB 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]