流体机械

2018, v.46;No.547(01) 20-24+33

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基于BP神经网络模型的磁悬浮水泵PID参数优化
PID Parameters Optimization on Magnetic Suspension Pump Based on the BP Neural Network Model

苏一新;马彦会;石倩;薛术;于溯源;
SU Yi-xin;MA Yan-hui;SHI Qian;XUE Shu;YU Su-yuan;Tsinghua University;

摘要(Abstract):

为了设计动态性能更优的磁悬浮水泵磁轴承支撑系统,本文利用多功能磁悬浮试验平台,通过整定磁轴承PID控制参数实现了转轴的5自由度稳定悬浮,然后随机选取径向磁轴承B的Y方向进行辨识试验,建立了其控制系统被控对象的BP神经网络模型,并采用Simulink进行PID参数优化,最后模拟磁悬浮水泵3种不同工况进行控制仿真对比。使用优化参数的系统仿真结果显示系统响应更快,试验结果表明,0~4000 r/min慢扫频过程中,转子X、Y方向位移分别降低了32.9%和24.1%,试验结果为磁悬浮水泵的PID参数优化提供了一种方法。
To design better performance dynamic of magnetic bearing support system of magnetic suspension pump, the multifunction magnetic levitation experiment platform was used to realize the 5-DOF stability suspension of the rotating shaft by setting the PID control parameters of the magnetic bearing. Then,the Y-direction of the radial magnetic bearing B was randomly selected to identify the BP neural network model of the controlled object,and PID parameters were optimized by Simulink. Finally,the simulation and comparison under three different working conditions were carried out. The simulation results show that the response of the system with optimized parameters is faster. And the experimental results show that the rotor's displacement in X and Y direction are reduced by 32.9% and 24.1% respectively in the course of 0~4000 r/min. This article provides a novel method for optimizing the PID parameters of the magnetic suspension pump.

关键词(KeyWords): 磁悬浮水泵;神经网络;系统辨识控制仿真;参数优化
magnetic suspension pump;neural network;system identification;control and simulation;parameter optimization

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基金项目(Foundation): 国家重点研发计划项目(2016YFC0202702)

作者(Author): 苏一新;马彦会;石倩;薛术;于溯源;
SU Yi-xin;MA Yan-hui;SHI Qian;XUE Shu;YU Su-yuan;Tsinghua University;

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