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基于混合控制集预测控制的永磁同步电机电流脉动抑制方法

程坦 苏宗昱 郑伟 牛建平

电机与控制应用2017,Vol.44Issue(10):1-7,12,8.
电机与控制应用2017,Vol.44Issue(10):1-7,12,8.

基于混合控制集预测控制的永磁同步电机电流脉动抑制方法

PMSM Current Ripple Suppression Method Based on Mixing Control Set Model Predictive Control

程坦 1苏宗昱 1郑伟 1牛建平2

作者信息

  • 1. 国网辽宁省电力有限本溪供电公司,辽宁本溪117000
  • 2. 沈阳大学电气工程学院,辽宁沈阳110000
  • 折叠

摘要

Abstract

In recent years,model predictive control technology (MPC) widely used in the high dynamic performance of motor drive system,in order to overcome the traditional MPC technology limited control set (FCS) steady current pulsation problem,a kind of based on mixing control set (MCS) predictive control method of all-digital fuzzy current ripple suppression was put forward.First of all,the analysis of discrete mathematics model all-digital fuzzy predictive control system,and the precision of voltage vector and the correlation between current ripple was analyzed.On this basis,the MCS-MPC would voltage source inverter limited number of effective voltage vector,extended to multiple compared with the form of virtual voltage vector,and based on the above online virtual voltage vector to complete the MPC optimization problem;In addition,considering the MCS-MPC system parameter sensitivity problem,analyzed the MCS-MPC system feedback noise problems were discussed.Finally,set up double 15 kW permanent magnet synchronous motor for prototype test platform for experimental analysis,content analysis including the MCS method of dynamic characteristics,current ripple effect of the steady state.The experimental results showed that the proposed MCS-MPC method in retained the traditional predictive control technology,on the basis of high dynamic response,which could effectively reduce the noise of all-digital fuzzy steady current pulsation and operation.

关键词

永磁同步电机/模型预测控制/混合控制集/电流脉动抑制

Key words

permanent magnet synchronous motor (PMSM)/model predictive control (MPC)/mixing control set (MCS)/current ripple suppression

分类

信息技术与安全科学

引用本文复制引用

程坦,苏宗昱,郑伟,牛建平..基于混合控制集预测控制的永磁同步电机电流脉动抑制方法[J].电机与控制应用,2017,44(10):1-7,12,8.

基金项目

国家自然科学基金资助项目(50274052) (50274052)

电机与控制应用

OACSTPCD

1673-6540

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