基于等价输入干扰估计器的PMSM自抗扰控制

合集下载

PMSM自抗扰控制算法研究

PMSM自抗扰控制算法研究杨会玲【摘要】The scheme of model-compensation of active disturbances rejection control was proposed pertaining to the existed problems in the PMSM speed regulation with one order active disturbances rejec-tion control algorithm. The overall model-compensation scheme boasts good anti-disturbance capacity compared to the one order algorithm.%介绍了自抗扰控制算法在永磁同步电机调速系统中的应用,针对一阶自抗扰控制算法在永磁同步电机调速系统中存在的问题,提出了模型补偿自抗扰控制方案. 相比一阶自抗扰控制算法,所采用的模型补偿自抗扰算法具有更好的抗扰动性能.【期刊名称】《工业仪表与自动化装置》【年(卷),期】2016(000)001【总页数】3页(P11-13)【关键词】自抗扰控制;永磁同步电机;调速;模型补偿【作者】杨会玲【作者单位】西安铁路职业技术学院牵引动力系,西安710014【正文语种】中文【中图分类】TP13自抗扰控制是近年来应用于电机控制中的一种新的非线性算法，能够实时估计并补偿系统的内外扰动，结合非线性控制策略，可以达到很好的控制品质。

与PI控制器相比具有较快的响应速度、较小的超调和较强的抗干扰能力。

标准的自抗扰控制器不需要知道对象的精确模型，只要知道了模型的阶次就可以设计出对象的自抗扰控制器。

但在有些复杂的应用场合，完全不利用被控对象模型进行系统设计，往往难以充分发挥出自抗扰控制方法的优点。

在PMSM调速系统中需要设计速度环的一阶自抗扰控制器［1－2］，若负载扰动较大，ESO则难以保证较高的估计精度，导致自抗扰控制器对扰动难以进行很好的补偿。

基于自抗扰控制的PMSM转速调节系统

基于自抗扰控制的PMSM转速调节系统崔国祥;张淼;陈思哲【期刊名称】《微特电机》【年(卷),期】2012(040)002【摘要】In the permanent magnet synchronous motor ( PMSM) speed control system,the dynamic response speed and overshoot is contradictory in classical PI regulator. ADRC was introduced into PMSM speed control. Tracking differentiator was adopted to set up a transition for the input, allowing the system work with good speed adaptability, and the extended state observer was used to enhance the robustness of the system by observing and real-time compensating general disturbance. Simulation results show that the speed control system based on PMSM using ADRC can follow the reference speed quickly without overshoot.%经典PI调节的永磁同步电动机转速控制,存在快速性与超调量之间的矛盾.将自抗扰控制技术应用于永磁同步电动机转速控制中,设计跟踪微分器对输入安排过渡过程,使系统有良好的转速适应性；扩张状态观测器通过对综合扰动项的观测和实时补偿,增强了系统的鲁棒性.仿真实验结果表明,基于ADRC的PMSM转速调节系统,可实现对输入信号的快速无超调跟踪.【总页数】4页(P51-54)【作者】崔国祥;张淼;陈思哲【作者单位】广东工业大学,广东广州510006;广东工业大学,广东广州510006;广东工业大学,广东广州510006【正文语种】中文【中图分类】TM351【相关文献】1.基于自抗扰控制的对称六相PMSM与三相PMSM串联系统 [J], 刘陵顺;韩浩鹏;闫红广;孔德彪;肖支才2.基于自抗扰控制器的PMSM伺服控制系统研究 [J], 肖泽民;朱景伟;夏野;赵英序3.基于扰动补偿的PMSM转速环自抗扰控制器设计 [J], 谢传林;曾岳南;王发良;曾祥彩4.基于自抗扰控制器的PMSM矢量控制系统设计与实现 [J], 刘清;王太勇;董靖川;刘清建;李勃5.基于模糊自抗扰控制在电动汽车PMSM位置驱动系统研究 [J], 李晶因版权原因，仅展示原文概要，查看原文内容请购买。

基于自抗扰控制技术的PMSM-DTC控制

制技术（DTC）。直接转矩控制技术将定子磁链
脉宽控制技术（SVPWM）。
和转矩作为控制变量，无需进行磁场定向、矢量
1 直接转矩控制原理
变化和电流控制，相对于矢量控制技术等现有控
制理论更加简捷快速，进一步提高了系统的动态
响应能力。但是，目前采用的基本的滞环比较控
制（Bang-Bang 控制）方法是利用 2 个滞环比较
torque control based on the switch table was improved，space vector pulse width modulation（SVPWM）and auto
disturbances rejection control（ADRC）technology were led in. The simulation results based on Matlab/Simulink show to
摘要：针对传统的永磁同步电机直接转矩控制（DTC）系统抗干扰性差、开关频率不稳定以及磁链脉动大
的问题，在基于开关表的直接转矩控制方法上进行改进，引进空间电压矢量脉宽调制技术（SVPWM）和自抗扰
控制技术（ADRC）。仿真结果显示：加入了自抗扰控制器以及空间电压矢量脉宽调制技术的永磁同步电机直
接转矩控制系统转矩脉动明显减小，系统抗干扰性增强，开关频率更加稳定。
ú
（1）
ê ú=ê
ê ú+ê
R + pL dúû ëi qû ëωΨ f û
ëu qû ë ωL q
te =
3p n |Ψ s |
[2Ψ f L q sin δ sf 4L d L q
|Ψ s |(L d - L q)sin(2δ sf )]

基于自抗扰技术的PMSM无位置传感器优化控制

基于自抗扰技术的PMSM无位置传感器优化控制
廖自力;赵其进;刘春光
【期刊名称】《微电机》
【年(卷),期】2018(051)007
【摘要】在使用优化的自抗扰控制(ADRC)代替传统比例积分(PI)控制的基础上,分别建立基于模型参考自适应法和脉振高频注入法的位置辨识系统,以满足永磁同步电机(PMSM)不同速度范围内的辨识精度需求.所设计的自抗扰控制器中,保留非线性微分跟踪器(TD)的同时以线性误差控制律代替非线性状态反馈控制律(NLSEF),使模型得以简化.仿真结果表明:简化后的ADRC能在两种无位置传感器控制方法中取得较好的控制效果,和PI控制相比,系统抗扰动性更强,电机位置和速度辨识效果也更优.
【总页数】5页(P44-47,53)
【作者】廖自力;赵其进;刘春光
【作者单位】陆军装甲兵学院控制工程系,北京100072;陆军装甲兵学院控制工程系,北京100072;陆军装甲兵学院控制工程系,北京100072
【正文语种】中文
【中图分类】TM351;TP273
【相关文献】
1.基于自抗扰控制的对称六相PMSM与三相PMSM串联系统 [J], 刘陵顺;韩浩鹏;闫红广;孔德彪;肖支才
2.基于模糊自抗扰的PMSM无速度传感器控制 [J], 黄庆;黄守道;匡江传;张志刚;李孟秋;罗德荣
3.基于自抗扰控制的船舶永磁电机无位置传感器混合控制 [J], 陈再发;刘彦呈;庄绪州
4.基于全阶自适应的PMSM无速度传感器抗扰控制 [J], 贾超广;肖海霞
5.基于自抗扰控制器的永磁同步电机无位置传感器矢量控制系统 [J], 孙凯;许镇琳;邹积勇
因版权原因，仅展示原文概要，查看原文内容请购买。

基于自抗扰控制PMSM电压空间矢量调制直接转矩控制方法

基于自抗扰控制PMSM电压空间矢量调制直接转矩控制方法刘英培【期刊名称】《电力自动化设备》【年(卷),期】2011(31)11【摘要】As the PID regulator has disadvantages and the direct torque control has higher torque and flux linkage ripples and unfixed switching frequency, the SVM (Space Vector Modulated) direct torque control for PMSM(Permanent Magnet Synchronous Motor) based on ADRC (Active-Disturbance Rejection Control) is proposed. The ADRC speed regulator is designed with the given speed and real speed as inputs and the given electromagnetic torque as output to improve the anti-interference ability of system. The realization of SVM is analyzed. The errors of torque and stator flux linkage are accurately compensated and ripples are reduced,while the constant switching frequency of inverter is guaranteed. Simulative and experimental results verify its feasibility and effectiveness.%针对PID调节器的不足及传统直接转矩控制转矩和磁链脉动大、开关频率不恒定等问题,提出基于自抗扰控制器(ADRC)永磁同步电机电压空间矢量调制(SVM)直接转矩控制方法.以给定转速和实际转速作为输入信号,给定电磁转矩作为输出信号,设计了ADRC速度调节器,提高系统的抗干扰能力.在此基础上,详细分析了SVM的实现方式,实现对转矩和磁链偏差的精确补偿,降低转矩和磁链脉动,并保证逆变器开关频率恒定.仿真和实验结果验证了方法的可行性和有效性.【总页数】5页(P78-82)【作者】刘英培【作者单位】华北电力大学电气与电子工程学院,河北保定071003【正文语种】中文【中图分类】TM301.2【相关文献】1.基于电压空间矢量调制技术的直接转矩控制 [J], 汤煊琳2.基于参考磁链电压空间矢量调制策略的永磁同步电机直接转矩控制研究 [J], 刘军;楚小刚;白华煜3.基于自抗扰控制的PMSM直接转矩控制研究 [J], 祁世民;周臻;窦晓华;王永4.基于自抗扰控制器的PMSM直接转矩伺服系统设计 [J], 黄艺香5.基于非线性自抗扰控制器的PMSM直接转矩控制 [J], 李少朋;谢源;张凯;贺耀庭因版权原因，仅展示原文概要，查看原文内容请购买。

自抗扰控制在PMSM伺服控制系统中的应用

自抗扰控制在PMSM伺服控制系统中的应用
杨兴华;姜建国
【期刊名称】《伺服控制》
【年(卷),期】2010(000)006
【摘要】永磁同步电机伺服控制系统的非线性和不确定性的特点,给高性能位置伺服控制的实现带来了困难。

为了克服电机及负载在内的广义被控对象不确定性因素和非线性因素对系统性能造成的影响,本文采用自抗扰控制器设计了伺服控制系统
的速度环和位置环。

自抗扰控制将系统所有扰动量,包括负载扰动、控制跟踪误差、模型误差等等,作为系统的一个状态变量,利用扩张状态观测器对扰动进行在线估计,并根据估计结果对扰动进行前馈补偿控制,从而抑制扰动对整个伺服控制系统的影响。

【总页数】5页(P36-39,42)
【作者】杨兴华;姜建国
【作者单位】上海交通大学电气工程系
【正文语种】中文
【中图分类】T
【相关文献】
1.神经网络优化自抗扰控制在供输弹系统中的应用 [J], 张松;王茂森;戴劲松
2.变增益策略在PMSM自抗扰控制中的应用与研究 [J], 李寅生;陈永军
3.优化自抗扰控制在刨花板施胶流量跟踪中的应用 [J], 郭继宁;孙丽萍;曹军;朱良
宽
4.自抗扰控制在加热器水位控制中的应用 [J], 张军亮;刘龙;史鹏飞;曹耀武;费盼峰;胡振亚
5.自抗扰控制在加热器水位控制中的应用 [J], 张军亮;刘龙;史鹏飞;曹耀武;费盼峰;胡振亚
因版权原因，仅展示原文概要，查看原文内容请购买。

基于自适应扰动观测器的PMSM_模型预测电流控制

第44卷第23期包装工程2023年12月PACKAGING ENGINEERING ·171·收稿日期：2023-02-13基于自适应扰动观测器的PMSM 模型预测电流控制金爱娟，张劲松，李少龙（上海理工大学，上海 200093）摘要：目的为了实现包装自动化生产线的高性能控制，针对永磁同步包装驱动电机在模型预测电流控制中对扰动敏感性较大的问题，设计一种基于自适应扰动观测器的模型预测电流控制策略。

方法利用预测误差设计一种自适应扰动观测器，对系统遭受的内部和外部的不确定扰动，扰动观测器估计总扰动并以电流的形式进行补偿。

将系统的瞬态过程和稳态过程分别进行考虑，设计一种含有动态权重因子的新型损失函数。

结果通过MATLAB/SIMULINK 仿真表明，与传统的控制方法相比，文中方法可以保持瞬态下的高速动态响应和稳态下的低电流纹波，并在应对参数失配和负载突变等问题上，展现了更好的稳态性能和抗干扰能力。

结论文中方法可以有效提升系统动态性能和鲁棒性，使改进后系统更加适用于包装机的应用场景。

关键词：永磁同步电机；自适应方法；扰动观测器；动态权重因子中图分类号：TB486；TM341 文献标识码：A 文章编号：1001-3563(2023)23-0171-10 DOI ：10.19554/ki.1001-3563.2023.23.021Predictive Current Control of PMSM Model Based on Adaptive Disturbance ObserverJIN Ai-juan, ZHANG Jin-song, LI Shao-long(University of Shanghai for Science and Technology, Shanghai 200093, China )ABSTRACT: The work aims to design a predictive current control strategy of model based on adaptive disturbance ob-server, in order to realize the high-performance control of the packaging automation production line and solve the problem that the permanent magnet synchronous packaging drive motor is more sensitive to disturbance in the predictive current control of model. Firstly, an adaptive disturbance observer was designed by the prediction error. For the internal and ex-ternal uncertain disturbances suffered by the system, the disturbance observer estimated the total disturbance and made compensation in the form of current. Moreover, the transient process and steady-state process of the system were consi-dered separately, and a new loss function with dynamic weight factors was designed. The MATLAB/SIMULINK simula-tion showed that, compared with the traditional control method, the method proposed could maintain high-speed dynamic response in transient state and low current ripple in steady state, and show excellent performance in coping with parameter mismatch and load mutation. It has better steady-state performance and anti-interference ability. The method proposed can effectively improve the dynamic performance and robustness of the system, making the improved system more suitable for the application scenarios of packaging machines.KEY WORDS: permanent magnet synchronous motor; adaptive method; disturbance observer; dynamic weighting factor未来五年是全面建设社会主义现代化国家开局起步的关键时期，包装印刷业也正在走向高质量发展的重要转型阶段。

基于并联RSO优化自抗扰的PMSM速度控制

CC

(８)

ｘ２＝ｘ１－ｂｕ

节代替ꎬ其表达式如式(４) 所示ꎮ
ｅ１＝ｖ１－ω ∗
ｍ
ω*m
(７)

ｘ２＝ａ ( ｔ)
由于ｘ１已知ꎬｘ２未知ꎬ构建出如下降阶观测器:
对于式(２) ꎬ将电机的运动方程简化为
{

ωm
z1
图１速度环线性自抗扰控制器结构
３并联降阶状态观测器速度控制
观测器的误差状态方程如下:

ｅ４＝ａ ( ｔ) －β０３ｅ４
(１２)
式(１２)的特征方程为ｄｅｔ(ｓ)＝ｓ＋β０３ ꎮ 因此ꎬ只要 β０３ >０ꎬ
同时扰动项ａ(ｔ)有界ꎬ那么降阶状态观测器就是稳定的[１１] ꎮ
３.２速度控制器设计
当扰动幅值较大时ꎬ 会存在一定的观测器误差 [１２] ꎮ
第一作者简介:付文强(１９９４—) ꎬ男ꎬ江西南昌人ꎬ硕士研究生ꎬ研究方向为电机控制ꎮ
１８４
付文强ꎬ等基于并联ＲＳＯ优化自抗扰的ＰＭＳＭ速度控制
电气与自动化
ｄω ｍ
ｄｔ
＝
ＴＬＢω ｍ
３
ｎ Ψｉ－－
２ＪｐｒｑＪ ∑ Ｊ ∑
(２)
式中Ｊ ∑ 为等效转动惯量ꎮ
影响ꎮ 因此ꎬ可对上述扩张状态观测器进行降阶处理ꎮ
ïｕ０＝ｋ１ｅ３
í
ï ＝－ｚ２
ïｕｕ０ｂ
î
z3
(６)
Байду номын сангаас1/s
-β03
x1(ωm)
-β203
控制器需要整定的参数分别为ｒ１、β０１、β０２、ｋ１ ꎮ 其中

基于扰动补偿的PMSM转速环自抗扰控制器设计

ｓｐｅｅｄｒｅｇｕｌａｔｉｏｎｓｙｓｔｅｍｂａｓｅｄｏｎｄｉｓｔｕｒｂａｎｃｅｃｏｍｐｅｎｓａｔｉｏｎｗａｓｄｅｓｉｇｎｅｄ．Ｕｓｉｎｇｔｈｅｉｄｅｎｔｉｉｆｃａｔｉｏｎａｌｇｏｉｒｔｈｍｔｏｉｄｅｎｔｉｆｙｔｈｅｌｏａｄｔｏｒｑｕｅａｎｄｍｏｍｅｎｔｏｆｉｎｅｒｔｉａ，ａｎｄｔｈｅｉｎｆｏｒｍａｔｉｏｎｗｈｉｃｈｃｏｌｌｅｃｔｅｄｗａｓｕｓｅｄｔｏｉｄｅｎｔｉｆｙｓｏｍｅｏｆｔｈｅｄｉｓｔｕｒｂａｎｃｅｉｔｅｍｓ
ｓｅｒｖｅｒ（ＥＳＯ）ｏｎｌｙｓｈｏｕｌｄｅｓｔｉｍａｔｅｔｈｅｒｅｓｉｄｕａｌｄｉｓｔｕｒｂａｎｃｅ．ＴｈｅａｍｏｕｎｔｏｆｄｉｓｔｕｒｂａｎｃｅｏｂｓｅｖｅｒｄｂｙＥＳＯｗａｓｒｅｄｕｃｅｄ，ａｎｄ
ＤｅｓｉｇｎｏｆＡｃｔｉｖｅＤｉｓｔｕｒｂａｎｃｅＲｅｊｅｃｔｉｏｎＣｏｎｔｒｏｌｌｅｒｆｏｒＰＭＳＭ
ＳｐｅｅｄＬｏｏｐＢａｓｅｄｏｎＤｉｓｔｕｒｂａｎｃｅＣｏｍｐｅｎｓａｔｉｏｎ

基于自抗扰控制器的PMSM直接转矩伺服系统设计

基于自抗扰控制器的PMSM直接转矩伺服系统设计黄艺香【摘要】在分析自抗扰控制理论的基础上，根据三相交流永磁同步伺服电机的非线性动态模型，介绍了以DSP及智能功率模块（IPM）实现的基于自抗扰控制器的PMSM直接转矩伺服系统实现方案，详述了该方案的硬件结构和软件设计。

系统控制电路采用DSP＋FPGA〔TMS320F2812＋EP1C6〕的CPU结构，功率电路以三菱IPM PS21867构成逆变器。

实验运行表明，采用自抗扰控制器伺服系统实时性好，具有较强的鲁棒性和适应性，良好动态性能。

硬件方案合理，结构通用紧凑。

【期刊名称】《黑龙江科技信息》【年(卷),期】2014(000)013【总页数】4页(P83-86)【关键词】永磁同步电机;自抗扰控制器;直接转矩控制;DSP;FPGA;IPM【作者】黄艺香【作者单位】南京林业大学，江苏南京 210037【正文语种】中文永磁同步电动机（PMSM）结构简单、功率密度大、效率高、转子损耗小，在医疗器械、家用电器等方面已经得到了广泛的应用，在各种高性能工业传动系统中也越来越受重视，特别在数控机床、工业机器人等小功率应用场合，永磁同步电动机伺服系统是主要的发展趋势。

现阶段，国内急需解决的主要问题就是控制器的国产化，如何研究并制造高性能、高可靠性的伺服系统有着重要的现实意义。

目前，永磁同步电机的控制方法主要有两种：矢量控制方法（VC）和直接转矩控制方法（DTC）。

矢量控制方法出现较早，技术比较成熟，其优点在于利用高性能的DSP和高精度的光电码盘转速传感器，调速范围可达1:1000，同时系统的动态性能也很好，是目前最常用的控制方法。

但它存在（1）计算复杂，需要作静止、旋转坐标变换，影响实时性；（2）转子磁场空间位置难精确定位，影响旋转坐标轴线定位及解耦效果等不足，由此造成实际系统的实现效果很难达到理论水平。

相比较矢量控制方法，直接转矩控制摒弃了解耦的思想，取消了旋转坐标变换，简单的通过电机定子电压和电流，借助瞬间空间矢量理论计算电机的磁链和转矩，并根据与给定值比较所得差值，实现磁链和转矩的直接控制。

于自抗扰技术的PMSM交流调速系统的研究

研究与设计Research and Design52 引言永磁同步电机在各类电机中，具有效率高、体积小、温升低、无需励磁绕组等诸多优点。

随着永磁同步电机在各种不同场合的应用日益广泛，其控制理论也不断成熟，先后形成了三种控制策略，分别为：恒压频比控制（VVVF ）、磁场定向控制（FOC-SVPWM ）、直接转矩控制（DTC ）[2]。

随着控制理论的不断发展，出现了以系统状态方程为研究对象的现代控制理论，在交流电机控制系统的研究中引进了诸多先进的控制策略，例如神经网络控制、自适应控制、模糊控制等，并且取得了一定的成果。

但现代控制算法往往计算复杂，对被控对象地精确数学模型依赖较强，难以应用到实际工程[4]。

ADRC 是一种新型的非线性控制器，综合了经典PID 控制器不依赖于被控对象具体数学模型的优点以及现代控制理论的设计方法[3]。

1 PMSM 数学模型介绍为实现PMSM 定子电流解耦控制，往往在交直轴坐标系下分析其数学模型，文献[4]指出，根据定子电压方程、磁链方程、电磁转矩方程以及机械运动方程，在i d =0 控制策略下，速度环以i q 作为对象输入，w r 为输出，可得如下微分方程：w J p i J p T J w R r n f q n l 2}=--X o （１．１）式中，p n 为极对数，J 为转动惯量，Ψf 为转子磁链，i q 为q 轴电流，T l 为负载转矩，w 为电角速度，R Ω为阻尼系数。

电流环以[u d u q ]T 作为输入， [i d i q ]T 为输出在dp 轴下可如下得微分方程： (1.2)()i i L R i i wi w i L L u u 1Wd qa a dq qd af a d q }=-+-+++o o ==>=G G H G 式中， L d =L q =L a 为交直轴电感，R a 为定子绕组，W 为系统未知扰动。

2 自抗扰控制器自抗扰控制技术是一种典型的基于误差来消除误差的控制策略，其最突出的特点就是把作用于被控对象的所有不确定因素都归结于未知扰动，然后用被控对象的输入、输出数据作为控制器输入，经过一系列运算处理，对此扰动进行在线估计与补偿。

基于自抗扰理论的PMSM电流环控制算法

基于自抗扰理论的PMSM电流环控制算法王福欣;郜世杰【摘要】针对传统的永磁同步电机(Permanent Magnet Synchronous Motor,PMSM)采用比例-积分-微分(Proportion-Integral-Derivative,PID)控制器进行电流控制,在恶劣环境下电流波动较大、稳定性较差的问题,提出一种基于自抗扰理论的PMSM电流环控制算法.采用自抗扰控制器(Active Disturbances Rejection Controller,ADRC)取代PMSM q轴电流环的PID控制器,并在MATLAB/Simulink中搭建ADRC模型,进行建模仿真.结果表明,将自抗扰理论应用到PMSM电流环的控制算法中,PMSM的电流波动更小,运行更平稳.【期刊名称】《上海船舶运输科学研究所学报》【年(卷),期】2018(041)003【总页数】5页(P24-28)【关键词】永磁同步电机;PID控制器;自抗扰控制器;电流环控制【作者】王福欣;郜世杰【作者单位】上海船舶运输科学研究所航运技术与安全国家重点实验室,上海200135;海军驻广州地区军事局,广州510000【正文语种】中文【中图分类】U664.1210 引言永磁同步电机（Permanent Magnet Synchronous Motor，PMSM）伺服控制系统一般采用三闭环结构（即速度环、位置环和电流环），其中电流环作为最内环结构，用来保证定子电流对电流指令的快速准确跟踪，其控制性能直接影响着位置环和速度环的控制性能，对于整个电机的控制而言具有重要作用。

目前在PMSM的磁场定向控制中，通常采用比例-积分-微分（Proportion-Integral-Derivative，PID）控制器分别对旋转坐标系的d轴和q轴进行控制，控制过程简单，容易得到实践[1]。

随着电路电子技术的发展，PID控制器在控制电流方面逐渐暴露出电流波动性较大、抵抗扰动的能力较差和稳定性不足等问题。

基于自抗扰控制器的PMSM矢量控制系统设计与实现

觶 1 = V2 V 觶 2 = fh V 觶 1 = Z2 - β1 ( Z1 - Y )+ b0U Z
(9)
(2) 扩张状态观测器 (10) 觶 2 =- β2 fal ( Z1 - Y , α1 , δ ) Z (3) 非线性误差反馈 U0 = β3 fal ( V1 - Z1 , α2 , δ ) (11) (4) 扰动补偿过程 U = U0 - Z2 (12) b0 式 (9) ~ 式 (12) 中 V1 是电流给定的跟踪值， Z1 是电流观测的跟踪值。使用 ESO 实时观测出系统 “ 内外扰动 ”
* 基金项目 : 国家自然科学基金项目（ 50975193 ）；国家科技重大专项 ( 2009ZX04014 - 101 - 05 ) ；天津市科技计划项目（ 08ZCKFGX02300 ）
1 ADRC 数学模型
自抗扰控制器是一种基于误差反馈的新型控制器，主要由非线性跟踪微分器 (NTD) 、扩张状态观测器 (ESO) 、
测控技术与仪器仪表
Measurement Control Technology and Instruments
基于自抗扰控制器的 PMSM 矢量控制系统设计与实现 *
刘清，王太勇，董靖川，刘清建，李勃（天津大学机械学院，天津 300072 ）
摘要：针对永磁同步电机存在的非线性、强耦合、参数摄动等问题，设计并实现了基于自抗扰控制器 (ADRC) 的矢量控制系统。首先提出基于 ADRC 的控制策略，实时观测出由系统内部非线性因素以及外部扰动引起的 “ 内外扰动 ” 并进行补偿，从而实现精确控制；其次研制基于 DSP 的多轴运动控制卡，并在此基础上实现了基于 ADRC 的 PMSM 矢量控制系统。仿真及实验结果表明，系统具有良好的动态性能及鲁棒性，能够快速加工出符合要求的模型。关键词：永磁同步电机；矢量控制；自抗扰控制器；非线性；

一种基于干扰观测器的非匹配干扰系统自抗扰控制方法与流程

一种基于干扰观测器的非匹配干扰系统自抗扰控制方法与流程下载温馨提示：该文档是我店铺精心编制而成，希望大家下载以后，能够帮助大家解决实际的问题。

文档下载后可定制随意修改，请根据实际需要进行相应的调整和使用，谢谢!并且，本店铺为大家提供各种各样类型的实用资料，如教育随笔、日记赏析、句子摘抄、古诗大全、经典美文、话题作文、工作总结、词语解析、文案摘录、其他资料等等，如想了解不同资料格式和写法，敬请关注!Download tips: This document is carefully compiled by the editor. I hope that after you download them, they can help you solve practical problems. The document can be customized and modified after downloading, please adjust and use it according to actual needs, thank you!In addition, our shop provides you with various types of practical materials, such as educational essays, diary appreciation, sentence excerpts, ancient poems, classic articles, topic composition, work summary, word parsing, copy excerpts, other materials and so on, want to know different data formats and writing methods, please pay attention!一种基于干扰观测器的非匹配干扰系统自抗扰控制方法与流程是一种新颖的控制策略，已经在许多工业领域得到广泛应用。

基于自抗扰控制器的PMSM伺服控制系统研究

基于自抗扰控制器的PMSM伺服控制系统研究肖泽民;朱景伟;夏野;赵英序【期刊名称】《微电机》【年(卷),期】2018(051)003【摘要】将自抗扰控制器(ADRC)应用在交流永磁同步电机(PMSM)伺服控制系统中,针对永磁同步电机伺服系统的高精度、快速响应等要求,对伺服控制系统三个闭环分别设计自抗扰控制器.在电流环设计一阶自抗扰控制器来取代常用的PID控制器,将位置环、速度环整合为一个统一的闭环并设计二阶自抗扰控制器进行控制;针对不同环节的控制要求和目的,采用不同的函数组合形式设计相应的控制器,充分利用自抗扰控制器的优良控制特性来满足高精度伺服控制系统的要求.通过搭建Simulink仿真模型进行验证,该伺服控制系统具有跟踪速度快、无超调、控制精度高、对负载及参数变化鲁棒性强等特点.【总页数】5页(P57-61)【作者】肖泽民;朱景伟;夏野;赵英序【作者单位】大连海事大学轮机工程学院,辽宁大连116026;大连海事大学轮机工程学院,辽宁大连116026;大连海事大学轮机工程学院,辽宁大连116026;大连海事大学轮机工程学院,辽宁大连116026【正文语种】中文【中图分类】TM351;TP273【相关文献】1.基于自抗扰控制器的PMSM无传感器控制 [J], 姚光耀;谭国俊;吴翔;刘光辉2.基于扰动补偿的PMSM转速环自抗扰控制器设计 [J], 谢传林;曾岳南;王发良;曾祥彩3.基于自抗扰控制器的PMSM矢量控制系统设计与实现 [J], 刘清;王太勇;董靖川;刘清建;李勃4.基于自抗扰控制器的PMSM直接转矩伺服系统设计 [J], 黄艺香5.基于非线性自抗扰控制器的PMSM直接转矩控制 [J], 李少朋;谢源;张凯;贺耀庭因版权原因，仅展示原文概要，查看原文内容请购买。

基于ESO的PMSM系统自抗扰FCS-MPC策略

基于ESO的PMSM系统自抗扰FCS-MPC策略张斌;汶雪;李坤奇【摘要】In order to improve the control performance of three-phase permanent magnet synchronous motor (PMSM)system, an active disturbance rej ection finite control set-mode predictive control (FCS-MPC)strategy based on improved extended state observer (ESO)is proposed in this paper.ESO is designed based on the arc-hyperbolic sine function to obtain estimations of rotating speed and back electromotive force (EMF)term of motor speed.Active disturbance rej ection control (ADRC)is applied as speed controller.The proposed FCS-MPC strategy aims to reduce the electromagnetic torque ripple and the complexity and calculation of the pared with the FCS-MPC strategy based on PI controller,the constructed control strategy can guarantee the reliable and stable operation of PMSM system,and has good speed tracking,anti-interference ability and robustness.%为了提高三相永磁同步电机(PMSM)系统的控制性能,以反双曲正弦函数为基础,通过改进的扩张状态观测器(ESO)获取转速和反电动势项高精度估值,以自抗扰控制作为转速控制调节器,提出了基于ESO的自抗扰有限控制集模型预测控制(FCS-MPC)策略,以减小电磁转矩脉动,降低算法的复杂性和计算量.与基于PI的 FCS-MPC策略相比,新的控制策略能够保证 PMSM系统稳定运行,具有良好的转速跟踪性、抗干扰性和鲁棒性.【期刊名称】《测试科学与仪器》【年(卷),期】2018(009)002【总页数】8页(P140-147)【关键词】扩张状态观测器;自抗扰控制;有限状态模型预测控制;永磁同步电机;反双曲正弦函数【作者】张斌;汶雪;李坤奇【作者单位】兰州交通大学自动化与电气工程学院,甘肃兰州730070;兰州交通大学自动化与电气工程学院,甘肃兰州730070;兰州交通大学自动化与电气工程学院,甘肃兰州730070【正文语种】中文【中图分类】TM3410 IntroductionThree-phase permanent magnet synchronous motor (PMSM) has many advantages such as simple structure, small volume, small moment of inertia and large power factor. So it has been widely used in important fields, such as transportation, military, industrial, medical and aviation[1,2]. The control methods of high performance PMSM system consist of vector control (VC)[3], direct torque control (DTC)[4,5] and model predictive control[6,7]. In recent years, a kind of optimization control method finite control set-mode predictive control (FCS-MPC) has been paid wide attention. FCS-MPC can be divided into current prediction control and torque prediction control[8,11] according to the control target[9,10,12].In traditional torque prediction control, it is necessary to adjust the weightcoefficient to ensure that the system has good dynamic performance, duing to the inconsistency between the stator flux and the electromagnetic torque[13]. In contrast, current prediction control has the same magnitude with the current variable, which can avoid to design weight coefficient. The traditional FCS-MPC needs to predict current values corresponding to all the basic voltage vectors in each sampling period, which makes it have heavy computing in the actual industrial control[14]. Zhang Y C[10] proposes a fast vector selection based on FCS-MPC, which reduces the complexity of computation and algorithm. As the back electromotive force (EMF) is DC amount, the method that estimates the back EMF of the current moment by calculating the values of the first three moments and averaging them will increase system complexity. Meanwhile, external interference will lead to estimation error. In this paper, the extended state observer (ESO) is applied to observe the back EMF in real time, and a new FCS-MPC strategy is constructed to improve the control performance of the system.FCS-MPC speed control system of PMSM requires accurate rotational speed information. The speed sensor with higher accuracy and resolution is expensive, and there are problems such as complexity of the system, noise quantization and so on. Therefore, the study of speed sensorless has drawn great attention. At present, the speed control methods of the motor system consist of high frequency injection (HFI)[15], extended kalman filter method (EKF)[16], model reference adaptive control (MRAS)[17], sliding mode (SM) variable structure[18] and extended state observer (ESO)[19].The arc-hyperbolic sine function of many speed identification methods can make ESO have a good estimation effect, and the ESO based on the arc-hyperbolic sine function, which does not need accurate mathematical model, has strong anti-jamming capacity and rapid convergency and so on. Speed regulator in FCS-MPC system of PMSM usually adopts PI algorithm. The control effect can be obtained by adjusting the PI parameters at different speeds and external disturbances. In order to improve the robustness of the system speed regulator, the authors proposed a new anti-disturbance rejection control strategy based on the arc-hyperbolic sine function[19-21] in recent years which has drawn wide concern. In the Ref.[20], the tracking differentiator of the arc-hyperbolic sine function is presented, in which the ideal differential signal can be obtained, and track response speed is quickly and stably. In Ref.[19], an extended state observer based on the arc-hyperbolic sine function is put forward. The observer can accurately observe the disturbance variable, and the response speed of the system is fast and stable. At the same time, the initial parameters of ESO can be used to suppress the differential amplitude. Active disturbance rejection control (ADRC), which does not require accurate mathematical models, has strong robustness and immunity. Therefore, ADRC based on arc-hyperbolic sine function is used as the speed regulator in this paper.In order to improve the control precision, robustness and control performance of the system, the ADRC FCS-MPC strategy based on ESO is proposed for PMSM system, which can reduce the cost of sensor at thesame time.1 Mathematical model of PMSMIn this paper, taking the surface mounted PMSM system as the control object, that is Ld=Lq=L, so the mathematical model in the synchronous rotating reference frame is(1)where id, iq and ud, uq are d, q axis currents and voltages of stators; Rs is stator resistor; Ls is stator inductance; ed, eq is back EMF; ωr is rotor velocity; ωe is electrical angular velocity; P is pole pairs; ψf is rotor permanent magnetic flux; TL is load torque; J is moment of inertia; and B is coefficient of friction factor.2 ADRC FCS-MPC strategy of PMSM system based on ESOFor the three-phase PMSM system, the system block diagram of active-disturbance rejection FCS-MPC based on ESO is shown in Fig.1.Fig.1 System block diagram of active disturbance rejection FCS-MPC strategy based on ESO2.1 Design of speed observer based on ESOAccording to the principle of stator current state Eq.(1) of PMSM and ESO, the first order state space equation of the system is constructed as(2)wherev1=[id iq],u=[ud uq],h=[-ed/L -eq/L],And h in Eq.(2) is extended to the new state variable v2, where q is present, and q(t) is bounded. The extended equation of Eq.(2) is(3)Eq.(3) is observable, and the second-order ESO of Eq.(3) can be constructed as(4)where β1>0, β2>0, β3>0, and arsh(·) is a smooth continuous nonlinear function.In the second-order ESO of Eq.(4), there are(5)where are the estimated values of id, iq; are the estimated values of counter electromotive items.The observed value of ESO contains the information of speed, i.e.,(6)where are the estimated values of ψd, ψq. The estimated value and position can be obtained as(7)2.2 Design of active disturbance rejection speed regulator based on arc-hyperbolic sine functionADRC consists of first-order tracking differentiator (TD), ESO and state error feedback control law. The speed tracking error can be reduced through the first step tracking differential. The system state and perturbation can be estimated by ESO in real time. The disturbance can be compensated by means of the state error feedback control law according to the separation principle. The structure is shown in Fig.2.Fig.2 Speed controller based on ADRC of PMSM system2.2.1 Design of first order tracking differentiatorA differential equation of first order speed tracking is constructed by using arsh(·)[20] as(8)where ωm is speed setpoint value, w is the transition variable, parameters b1>0, a1>0. a1 is close to 1 in usual. The appropriate increase of b1 can increase the response speed and reduce the tracking error. The idealresponse output of ωm can be obtained by Eq.(8).2.2.2 Design of second-order ESOLetx1=ωr, y2=x1.(9)According to the speed differential equation constructed by Eq.(1), the first order state space equation is constructed as(10)where b0=1.5ψfP/J, y2 is the input of speed controller, iq is the output of speed controller.From Eq.(10), we can see that the load torque and viscous friction coefficient are changing interference signals. The various unknown disturbances are denoted by f(t) asf(t)=-Bωr/J-TL/J.(11)Let x2(t)=f(x1), and x2(t) is extended variable, that is The first order system constructed by Eq.(10) is extended to(12)The second-order extended state observer of the structural system constructed by Eq.(12) is(13)where b2>0, b3>0, a2>0. a2 is close to 1 in usual. The astringency of ESO is easy to be influenced by parameter b2. The extended state observer constructed by Eq.(13) can achieve accurate state variable estimation of the expansion Eq.(12) only when b2-b3a2>0, that is z1(t)→x1(t), z2(t)→x2(t).2.2.3 First-order active-disturbance rejection controllerThe error feedback control rate u0(t) shown in Fig.2 is used to feed forward the interference signal. It is designed as(14)where parameters b4>0, a3>0. a3 is close to 1 in usual. A small ripple of control quantity u can be got by selecting the proper value of b4.2.3 FCS-MPC based on fast vector selectionAccording to Eqs.(1) and (6), the current space state vector differential equation under the selected rotation coordinate axis is constructed asis=(us-Rsis)/Ls-z2,(15)where is=[id iq] is current vector; us=[ud uq] is voltage vector.2.3.1 Current model predictive control based on fast vector selectionThe traditional FCS-MPC calculates the predicted current for each fundamental voltage vector in the rotating coordinate system first, andthen calculates the corresponding minimum objective function value based on the predicted current, finally selects the voltage vector of the minimum objective function as the best output of the inverter. But it needs to forecast current for 7 times, which makes the amount of calculation relatively large. In order to obtain better control effect, the FCS-MPC strategy based on fast vector selection is presented in Ref.[10], in which the optimal voltage vector is obtained fast by summing the average to estimate the back EMF. Therefore, complexity of the algorithm and the computation is obviously reduced. However, the estimation of back EMF will increase the complexity of the computation and system, and external interference will lead to estimation error. In this paper, the Eq.(5) is used to estimate the back EMF.In this paper, the second-order Eulerian discretization method is applied to further simplify the Eq.(10)[10], that is(16)whereIn Eq.(16), the ideal voltage vector is obtained when i.e.,(17)Let uk(k=1,2,…,6) be the the base voltage vector of 6 sectors, and as longas the amplitude of the error vector is the smallest, i.e.,(18)When the output basic voltage vector is zero vector, the amplitude of the error vector is(19)The method can be summarized as follows: (1) is calculated by Eq.(17). (2) Judging the sector k (k=1,2,…,6) that located by Eq.(18). (3) Comparing e0 with euk by Eqs.(18) and (19). If e0>euk, the best voltage vector is euk, otherwise, the best voltage vector is e0.2.3.2 Control of delay compensationThe actual output voltage of the controller lags the current change in the actual digital system control[22]. To eliminate the negative effect of the system control performance by the delay, is calculated according to Eq.(36) in Ref.[14], and then the voltage is compensated at k+1 by appling the second-order Euler discretization method, which compensates the delay of the system.(20)The flow diagram of FCS-MPC based on fast vector selection is shown in Fig.3 with considering the delay compensation.Fig.3 FCS-MPC flow chart based on fast vector selection3 Simulation analysisThe model of Fig.1 is structured and simulated in Matlab/Simulink environment. The simulation parameters of PMSM system are shown in Table 1. The sampling period of the system is 10 μs. In o rder to verify the correctness and validity of the active-disturbing FCS-MPC method of PMSM system based on ESO, two FCS-MPC systems based on PI and ADRC are constructed by appling the same speed ESO parameters, and they are compared and analyzed.Table 1 Parameters of PMSMParameterSymbolDataStatorresistanceRs(Ω)3．45Windinginductanc eLs(H)0．012RatedpowerPN(kW)1．1FrictioncoefficientBm0．05PolepairP2 MomentofinertiaJ(kg·m2)0．00154RatedtorqueTN(N·m)3DCpowersupplyU dc(V)380RatedspeedωN(r/min)10003.1 Comparison of anti-load abilityAdjusting PI parameters to obtain the same transient of the two systems so that they can meet the rationality comparison. When simulation, the speed setpoint of PMSM system is 1 000 r/min, the PMSM system starts with load (1 N·m) and is loaded to the rated load (3 N·m) at 0.2 s. The response curves of two systems are shown in Figs.4 and 5, respectively. Fig.4 Dynamic response of speed sensorless PMSM system based on PI FCS-MPC strategySimulation analyses are as follows.1) ESO speed estimation. As can be seen from Figs.4 and 5(a) and (b), both the FCS-MPC PMSM systems based on PI and ADRC, the ESO speed estimates and the actual curves are almost coincident, and the speed errors are small, i.e., the speed observer can be quickly tracked and has a high recognition accuracy.2) Robustness of ative-disturbance FCS-MPC strategy for three-phase PMSM. Figs.4 and 5(a) show that the FCS-MPC PMSM system based on ADRC has smaller torque ripple and can be restored to the reference value, which means that it has a stronger anti-load capacity comparing with the FCS-MPC PMSM system based on PI. As can be seen from Figs.4 and 5(c), the FCS-MPC PMSM system based on PI has the smaller electromagnetic torque ripple compared to the FCS-MPC PMSM system based on ADRC. Fig.5 Dynamic response of PMSM system based on ADRC with FCS-MPC strategy3.2 Comparison of transient response characteristicsPI parameters are adjusted so that two FCS-MPC PMSM systems based on PI and ADRC have the same anti-load change capability as possible for which can meet the rationality comparison. When simulation, the speed setpoint of PMSM system is 1 000 r/min, the PMSM system start with load (1 N·m) and is loaded to the rated load (3 N·m) at 0.2 s. The response curves of two systems are shown in Figs.6 and 7, respectively.The following results can be obtained by simulation analysis.1) ESO speed estimation. As can be seen from Figs.6 and 7(a) and (b), boththe FCS-MPC PMSM systems based on PI and ADRC, the ESO speed estimates and the actual curves are almost coincident, and the speed errors are small, that is, the speed observer can be quickly tracked and has a high recognition accuracy.Fig.6 Dynamic response of FCS-MPC strategy on speed sensorless PMSM system based on PI2) Robustness of active-disturbance FCS-MPC strategy for three-phase PMSM. From Figs.6 and 7(a), the FCS-MPC PMSM system based on ADRC has smaller overshoot and shorter control period when the resistance to load change is consistent, and it has better speed transient response characteristics. As can be seen from Figs.6 and 7(c), the FCS-MPC PMSM system based on PI has the smaller electromagnetic torque ripple compared to the FCS-MPC PMSM system based on ADRC.Above all, the control method designed in this paper can guarantee the stable operation of the system when the load changes, and it can ensure the system has strong anti-load interference ability, low electromagnetic torque ripple, and good dynamic performance. It does better than PI control in the anti-load capacity and dynamic performance.Fig.7 Dynamic response of FCS-MPC strategy of speed sensorless PMSM system based on ADRC4 ConclusionIn this paper, an active-disturbance-rejection FCS-MPC strategy based on ESO speed sensorless of surface mounted PMSM was proposed. ESO based on arsh(·) is designed to estimate the speed and back EMF termaccurately. Compared with the PI-based FCS-MPC system, it can ensure that the system has strong anti-load interference ability, small electromagnetic torque ripple and good dynamic performance, which can achieve satisfactory torque and speed control effect. Actual results indicate the correctness and feasibility of the proposed method.References[1] Dai Y, Song L, Cui S. Development of PMSM drives for hybrid electric car applications. IEEE Car Transactionson Magnetics, 2007, 43(1)： 434-437.[2] Xia C L, Yan Y. Matrix converter permanentmagnet synchronous motor drives.Transactionof China Eletrotechnical Society, 2015, 30(23)： 1-9. [3] Rashed M, Macconnell P F A, Stroncach A, et al. Sensorless indirect rotor field orientation speed control of permanent magnet synchronous motor using adaptive rotor flux estimator. In: Proceedings of the 44th IEEE Conference on Decision and Control, 2005.[4] Simanek J, Novak J, Cerny O, et al. FOC and flux weakening for traction drive with permanent magnet synchronous motor. In: Proceedings of IEEE International Symposium on Industrial Electronics. IEEE Xplore, 2008：753-758.[5] Foo G, Sayeef S, Rahman M F. Low-speed and standstill operation of a sensorless direct torque and flux controlled IPM synchronous motor drive.IEEE Transactions on Energy Conversion, 2010, 25(1)： 25-33.[6] Rodriguez J, Cortes P. Predictive control of power converters and electrical drives. Predictive Control of Power Converters & Electrical Drives, 2012, 6(4)： 1785-1786.[7] Moon H T, Kim H S, Youn M J. A discrete-time predictive current control for PMSM. IEEE Transactions on Power Electronics, 2003, 18(1)： 464-472.[8] Geyer T, Papafotiou G, Morari M. Model predictive direct torque control—Part I： concept, algorithm, and analysis. IEEE Transactions on Industrial Electronics, 2009, 56(6)： 1894-1905.[9] Preindl M, Schaltz E. Sensorless model predictive direct current control using novel second-order pllobserver for pmsm drive systems. Industrial Electronics IEEE Transactions on, 2011, 58(9)： 4087-4095.[10] Zhang Y C, Yang H T, Wei X L. Prediction control of permanent magnet synchronous motor model based on fast vector selection. Journal of Electrical Engineering, 2016, 31(6)： 66-73.[11] Rodriguez J, Kennel R M, Espinoza J R, et al. High performance control strategies for electrical drives： an experimental assessment. IEEE Transactions on Industrial Electronics, 2012, 59(5)： 812-820.[12] Morel F, Lin S X, Retif J M, et al. A comparative study of predictive current control schemes for a permanent magnet synchronous machine drive. IEEE Transactions on Industrial Electronics, 2009, 56(7)： 2715-2728.[13] Cortes P, Kouro S, La Rocca B, et al. Guidelines forweighting factors design in Model Predictive Control of power converters and drives. IEEE International Conference on Industrial Technology, 2009： 1-7.[14] Zhang Y C, Gao S Y. Measurement and prediction ofpermanent magnet synchronous motor considering delay compensation. Journal of Electrical Engineering, 2016, 11(3)： 13-20.[15] Zhu Z Q, Gong L M. Investigation of effectiveness of sensorlessoperation in carrier signal-injection-based sensorless controlmethod-s. IEEE Transactions on Industrial Electronics, 2011, 58(8)： 3431-3439. [16] Smidl V, Peroutka Z. Reduced-order square-root EKF for sensorless control of PMSM drives. Conference of the IEEE Industrial Electronics Society, 2011, 6854(5)： 2000-2005.[17] Orlowska K T, Dybkowski M. Stator-current-based mras estimator for a wide range speed sensorless induction-motor drive. IEEE Transactions on Industrial Electronics, 2010, 57(4)： 1296-1308.[18] Teng Q F, Bai J Y, Zhu J G, et al.Predictive torque control of three phase permanent magnet synchronous motor based on sliding mode modelreference adaptive observer.Control Theory & Applications, 2015, 32(2)： 150-161.[19] Zhou T. Expansive state observer based on inverse hyperbolic sine function. Control and Decision, 2015, 30(5)： 943-946.[20] Zhao T. Study on tracking differentials based on inverse hyperbolic sine function.Control and Decision, 2014, 29(6)： 1139-1142.[21] Zhao L Y, Wang S J. Automatic disturbance control based on arctangent nonlinear function. Journal of Shanghai Jiaotong University, 2013, 47(7)： 1043-1048.[22] Miranda H, Cortes P, Yuz J I, et al. Predictive torque control of induction machines based on state space models. IEEE Transactions on Industrial Electronics, 2009, 56(6)： 1916-1924.。

1、下载文档前请自行甄别文档内容的完整性，平台不提供额外的编辑、内容补充、找答案等附加服务。
2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
3、如文档侵犯您的权益，请联系客服反馈,我们会尽快为您处理(人工客服工作时间：9:00-18:30)。

Ｋｅｏｄｓ：Ｓ；ｙｗｒＰＭＭＡＤＲＣ；ｑｕｖｌｎｎｔｄｉｔｒｎｃｓｉｔｒｄｉｅｔｆｅｂａｋｌｎａｉａｉｎｅｉａｅｔｉｐｕｓｕｂａｅｅｔｍａｏ；ｒｃｅｄｃｉｅｒｚｔｏ
０引言
随着永磁磁性材料、导体功率器件的发展，半永
关键词：永磁同步电动机；自抗扰控制；等价输入十扰估计器；直接反馈线性化
中图分类号：Ｍ３１Ｔ４文献标识码：Ａ文章编号：０４７１（００）９０４ — ４１０ — ０８２１０ — ０３０
ＡｃｉｅＤｓｕｂｎｅＲｅｅｔｎＣｎｒｌｏＭＳａｅｎＥｕｖｌｎｎｕｉｕｂｎｅＥｔｔｒｔｉｒａｃｊｃｉｏｔｏｒＰＭｓＢｓｄｏｑｉａｅｔＩｐｔＤｓｒａｃｓｍａｏｖｔｏｆｔｉ
议持电棚２０第期０年９ｌ
… … … … ＿－一－ … … … ＿－… － … … … … … … … … … 一 … … 一 … … … … … … … … … … … … … －ｃ／／
驱动
ｄ … 一。
基于等价输入干扰估计器的ＰＳ自抗扰控制ＭＭ
磁同步电动机（以下简称ＰＳ由于其结构紧凑、ＭＭ）高功率密度、高气隙磁通和高转矩惯性比等优点，在伺服系统中得到广泛应用。针对永磁同步交流伺服系统，传统ＰＤ控制策略控制简单、于实现，本Ｉ易但
道，以便于设计系统的扰动抑制算法。本文将自抗扰控制。思想与等价输入干扰估计方法相结合，。
构成了新型白抗扰控制器，于ＰＭ的速度控用ＭＳ制¨ ‘中。该方法继承了自抗扰控制的大部分优点，
ＷＵＺｅｇ— ｈｎ）ｈ — ｈｎｈｎｃｅｇ，ＩＺｉｃｅｇ
（ｉｎｎｎＵｉｅｉ，ｘ２４２ＣｉａＪｇａｎｖｒｔＷｕｉ１１２，ｈｎ）ａｓｙ
Ａｓｒｃ：ＡＨｗａｔｅｄｓｒａｃｅｔｎｃｎｒｂｔａｔｅｃｖｉｕｂｎｅｉｔｃｉｏｔｌ（ＤＣ）ｓｓｍｏｐｒｎｎｍｇｅｓｎｈｏｏｓｍｔｓｏｏＡＲｙｔｆｅｍａｅｔａｎｔｙｃｒｎｕｏｏｅｒ（ＭＳｓａｅＨｅｕｌｔｎｕｄｓｒａｃｓｍｔａｒｓｎｅ．ｕｊｔｏｍｔｅａｃｎｄｌｆＭＳｆｒｉＰＭ）ｂｓｄＯｑｉｅｐｔｉｕｂｎｅｅｔａｏｗｓｅｅｔｄＳｂｃｔａｍｔｉｅｏＰＭｓｔ — ａｎｉｔｉｒｐｅｈｉｏａｅｄｒｃｆｅｂｃｎａｉｔｎｔｃｉｇｄｆｒｎｉｏＴｅｔｅｄａｋｌｅｒａｏ，ａｋｎ — ｉｅｅｔｔｉｚｉｒｆａｒ（Ｄ）ａｄｎｎｉｅｒｔｅｅｒｒｅｂｅ（ＬＥ）ｗｒａｏｔａ— ｎｏｌａａｒ￣ｄａｋＮＳＦｅｅｄｐｄｔｅｌｎｓｔｏｅｏ
ｃｌｔｏｔｌｑａｔｙａｄｔｅｅｕｖｌｎｐｔｄｓｒａｃｓｉｔｒｓｉｔｄｃｄｔｓｉｔｎｎｗｉｔｒａｃ．Ｓｍ— ｕａｅｃｎｒｕｎｉｎｈｑｉａｅｔｎｕｉｔｂｎｅｅｔｏｔｉｕｍａｏｎｒｕｅｅｔｗａｏｏｍａｅｕｋｏｎｄｓｂｎｅｉｕｕａｉｎｒｓｌｌｓｒｔｈｔｔｉｏｔｌｒｃｎｅｔｔｎｆｃｉｅｙｒｓｒｉｎｎｗｉｔｒａｃｆｔｅｓｓｅｌｔｅｕｔｉｕｔａｅｔａｈｓｃｎｒｌａｓｉｅａｄｅｆｔｌｅｔａｎｕｋｏｎｄｓｕｂｎｅｏｙｔｍ．ｏｓｌｏｅｍａｅｖｈ
身是依据线性设计思想，制系统动态性能中 “ 控快速性 ” 超调量 ” 两个难以调和的矛盾，制和“ 是控器参数不易调节，且抑制参数摄动性能不理想，并难
控制器参数调节方便，有系统响应 “ 速性 ” 没快与 “ 调” 超的矛盾，于工程实现。仿真结果表明，易该
吴正成，志成纪
（江南大学，江苏无锡２４２）１１２摘要：设计ｒ一种基于等价输入ｆ扰估计器的新型自抗扰控制系统，用于永磁同步电动机的速度控制。该
系统运用跟踪微分器和非线性状态误差反馈控制器产生控制量，并引入等价输人干扰估计器对系统未知＿扰作估．ｆ计补偿，针对直接反馈线性化后的ＰＭ模型进行速度控制。仿真结果表明该控制器能够有效估计并抑制系统未ＭＳ知干扰，系统响应快，稳态精度高。
系统设计方法响应快、超调小，比传统的方法具有更好的稳定性和抗干扰能力。