|本期目录/Table of Contents|

[1]车海军,王亮亮,霍丽娇,等.改进的无功功率模型参考自适应异步电机转速辨识[J].电机与控制学报,2017,21(10):40-46.[doi:10.15938/j.emc.2017.10.006]
 CHE Hai-jun,WANG Liang-liang,HUO Li-jiao CUI Hui-hui,et al.Improved reactive power model reference adaptive speed identification applying to induction motor[J].,2017,21(10):40-46.[doi:10.15938/j.emc.2017.10.006]
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《电机与控制学报》[ISSN:1007-449X/CN:23-1 408/TM]

卷:
21
期数:
2017年10
页码:
40-46
栏目:
出版日期:
2017-10-01

文章信息/Info

Title:
Improved reactive power model reference adaptive speed identification applying to induction motor
作者:
?车海军12 王亮亮12 霍丽娇12 崔慧慧12 杨景明12
?(1. 燕山大学 国家冷轧板带装备及工艺工程技术研究中心,河北 秦皇岛 066004; 2. 燕山大学 工业计算机控制工程河北省重点实验室,河北 秦皇岛 066004)
Author(s):
?CHE Hai-jun 12 WANG Liang-liang 12 HUO Li-jiao 12 CUI Hui-hui 12 YANG Jing-ming 12
?(1. National Engineering Research Center for Equipment and Technology of Cold Strip Rolling of Hebei Province,Yanshan University,Qinhuangdao 066004,China; 2. Key Lab of Industrial Computer Control Engineering of Hebei Province,Yanshan University,Qinhuangdao 066004,China)
关键词:
转速辨识 模型参考自适应 无功功率 巴特沃斯滤波器 模糊 PI 控制器
Keywords:
speed identification model reference adaptive reactive power Butterworth filter fuzzy PI controller
分类号:
TM 452
DOI:
10.15938/j.emc.2017.10.006
文献标志码:
A
摘要:
?针对传统无功功率模型参考自适应模型的输入信号中含有大量的高频信号和噪声,致使模型的自适应机构设计难度增加、速度预测精确度降低的问题,提出改进的基于无功功率的模型参考自适应系统。在传统的无功功率模型参考自适应模型的基础上,引入巴特沃思滤波器并运用改进的模糊 PI 控制器取代原有的控制器,滤除了输入信号的噪声,提高转速预测精确度。仿真结果表明,改进后的无功功率模型参考自适应系统,参考模型输出的无功功率信号较滤波前其振动的幅值和频率大幅度降低,将这种信号作为自适应模块的输入得到的预测转速,其预测精确度和预测系统动态性能得到提高显著。
Abstract:
?The input signal of the traditional reactive power model reference adaptive model contains a large number of high-frequency signals and noises,which causes much difficulties to design the model of the adaptive and reducing the accuracy of the speed prediction. The improved reactive power model reference adaptive model is proposed to solve this problem. This model was based on the traditional reactive power model reference adaptive model,which introduced the Butterworth filter and an improved fuzzy PI controller to replace the original controller,filter out the input signal noise and improve speed prediction accuracy. Simulation results show,in the improved reactive power model reference adaptive system,the magnitude and frequency of the reactive power signal output from the reference model is significantly lower than those before filtering. This signal is used as input to the adaptive module and the predicted speed is got. The prediction accuracy and prediction system dynamic performance are significantly improved

参考文献/References:

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备注/Memo

备注/Memo:
?收稿日期: 2017 - 01 - 09
基金项目: 河北省高等学校创新团队领军人才培训计划( LJRC013) ; 河北省自然科学基金面上项目( F2016203249) ; 国家冷轧板带装备及工艺工程技术研究中心开放课题( 2012006)
?作者简介: 车海军( 1974—) ,男,博士生,副教授,研究方向为轧制自动化、交流电机智能控制、多目标优化; 王亮亮( 1992—) ,男,硕士研究生,研究方向为交流电机智能控制; 霍丽娇( 1991—) ,女,硕士研究生,研究方向为交流电机智能控制; 崔慧慧( 1992—) ,女,硕士研究生,研究方向为进化算法、多目标优化; 杨景明( 1957—) ,男,博士,博士生导师,研究方向为人工智能与神经网络应用、轧制过程自动控制、交流电机控制。
更新日期/Last Update: 2018-02-06