Article(id=1200394758871970295, tenantId=1146029695717560320, journalId=1189987059142926344, issueId=1200394757995360759, articleNumber=null, orderNo=null, doi=10.19457/j.1001-2095.dqcd25362, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1693929600000, receivedDateStr=2023-09-06, revisedDate=1699804800000, revisedDateStr=2023-11-13, acceptedDate=null, acceptedDateStr=null, onlineDate=1764126012770, onlineDateStr=2025-11-26, pubDate=1742400000000, pubDateStr=2025-03-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1764126012770, onlineIssueDateStr=2025-11-26, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1764126012770, creator=13701087609, updateTime=1764126012770, updator=13701087609, issue=Issue{id=1200394757995360759, tenantId=1146029695717560320, journalId=1189987059142926344, year='2025', volume='55', issue='3', pageStart='3', pageEnd='96', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1764126012562, creator=13701087609, updateTime=1764148644802, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1200489684553027930, tenantId=1146029695717560320, journalId=1189987059142926344, issueId=1200394757995360759, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1200489684553027931, tenantId=1146029695717560320, journalId=1189987059142926344, issueId=1200394757995360759, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=13, endPage=20, ext={EN=ArticleExt(id=1200394759140405754, articleId=1200394758871970295, tenantId=1146029695717560320, journalId=1189987059142926344, language=EN, title=An Asynchronous Motor Speed Regulation Method Based on a New Sliding Mode Reaching Law, columnId=null, journalTitle=Electric Drive, columnName=null, runingTitle=null, highlight=null, articleAbstract=

Aiming at the poor robustness and system vibration problem of asynchronous motors under the traditional sliding mode control,a variability coefficient power exponent reaching law (VCPERL) was proposed to dynamically change the control coefficients according to the position of the sliding mode surface,and the sliding mode controller was designed based on this reaching law. Firstly,according to the advantages of quick-power reaching law (QPRL) and the double-power reaching law (DPRL),which have different reaching rates at different positions of the sliding mode surface,meanwhile,the tanh(x)was used to replace the sign(x),and a variable coefficient was introduced into the reaching law. Secondly,the stability of the new reaching law was proved based on theoretical analysis and simulation. Finally,the VCPERL was applied to design the sliding mode controller according to the theory of vector control oriented by rotor magnetic chain and the dynamic mathematical model of asynchronous motor. The simulation results show that compared with the traditional PI control,QPRL and DPRL,VCPERL has strong immunity to load disturbances and fast recovery capability,which can effectively improve the dynamic response performance of the system.

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针对异步电机在传统滑模控制下的鲁棒性差和系统抖振问题,提出一种控制系数根据滑模面位置而动态变化的变系数幂指趋近律(VCPERL),并基于该趋近律设计滑模控制器。首先,考虑快速幂次趋近律(QPRL)和双幂次趋近律(DPRL)在滑模面不同位置趋近速率不同的优点,利用双曲正切函数tanh(x)替换符号函数sign(x),并在趋近律中引入变系数项,提出VCPERL。其次,根据理论分析和仿真,证明新型趋近律的稳定性。最后,根据转子磁链定向矢量控制理论和异步电机的动态数学模型,应用VCPERL设计滑模控制器。仿真结果表明,与传统PI控制、QPRL和DPRL相比,VCPERL对负载扰动具有强抗扰能力和快速恢复能力,可有效提高系统的动态响应性能。

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张蕊(1998—),男,硕士,主要研究方向为电力电子传动,Email:

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张蕊(1998—),男,硕士,主要研究方向为电力电子传动,Email:

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张蕊(1998—),男,硕士,主要研究方向为电力电子传动,Email:

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Parameters of the reaching law

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趋近律 参数数值
QPRL k1=10,k2=2,w1=0.2
DPRL k1=10,k2=2,w1=0.2,w2=1.5
VCPERL k1=10,k2=2,k3=0.001,w2=1.5,h=0.01,g=0.01
), ArticleFig(id=1200455238575575556, tenantId=1146029695717560320, journalId=1189987059142926344, articleId=1200394758871970295, language=CN, label=表1, caption=

趋近律参数

, figureFileSmall=null, figureFileBig=null, tableContent=
趋近律 参数数值
QPRL k1=10,k2=2,w1=0.2
DPRL k1=10,k2=2,w1=0.2,w2=1.5
VCPERL k1=10,k2=2,k3=0.001,w2=1.5,h=0.01,g=0.01
), ArticleFig(id=1200455238659461637, tenantId=1146029695717560320, journalId=1189987059142926344, articleId=1200394758871970295, language=EN, label=Tab.2, caption=

Reaching law parameters of the speed control system

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趋近律 参数数值
QPRL k1=450,k2=950,w1=0.5
DPRL k1=450,k2=950,w1=0.5,w2=2
VCPERL k1=450,k2=950,k3=0.2,w2=2,h=0.8,g=0.1
), ArticleFig(id=1200455238751736326, tenantId=1146029695717560320, journalId=1189987059142926344, articleId=1200394758871970295, language=CN, label=表2, caption=

调速系统趋近律参数

, figureFileSmall=null, figureFileBig=null, tableContent=
趋近律 参数数值
QPRL k1=450,k2=950,w1=0.5
DPRL k1=450,k2=950,w1=0.5,w2=2
VCPERL k1=450,k2=950,k3=0.2,w2=2,h=0.8,g=0.1
), ArticleFig(id=1200455238831428103, tenantId=1146029695717560320, journalId=1189987059142926344, articleId=1200394758871970295, language=EN, label=Tab.3, caption=

Dynamic following performance indicators

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系统名称 上升时间tr/ms 调节时间ts/ms 转速最大值
nmax/(r·min-1
稳态静差/(r·min-1
VCPERL 75.0 81 803.3 0.07
QPRL 75.4 85 804.5 0.16
DPRL 75.5 82 803.3 0.19
PI 75.8 92 803.5 0.13
), ArticleFig(id=1200455238911119880, tenantId=1146029695717560320, journalId=1189987059142926344, articleId=1200394758871970295, language=CN, label=表3, caption=

动态跟随性能指标

, figureFileSmall=null, figureFileBig=null, tableContent=
系统名称 上升时间tr/ms 调节时间ts/ms 转速最大值
nmax/(r·min-1
稳态静差/(r·min-1
VCPERL 75.0 81 803.3 0.07
QPRL 75.4 85 804.5 0.16
DPRL 75.5 82 803.3 0.19
PI 75.8 92 803.5 0.13
), ArticleFig(id=1200455238978228745, tenantId=1146029695717560320, journalId=1189987059142926344, articleId=1200394758871970295, language=EN, label=Tab.4, caption=

Dynamic immunity performance indicators

, figureFileSmall=null, figureFileBig=null, tableContent=
控制
方式
负载转矩增加 负载转矩减少
动态
速降/
(r·min-1
稳态
误差/
(r·min-1
恢复
时间
/ms
动态
速升/
(r·min-1
稳态
误差/
(r·min-1
恢复
时间/ms
VCPERL 5.05 0.07 5.7 1.67 0.07 4.3
QPRL 5.3 0.15 10.3 2.67 0.22 7.1
DPRL 5.1 0.15 6.1 1.68 0.21 4.8
PI 5.25 0.02 15.5 1.99 0.11 12.6
), ArticleFig(id=1200455239053726218, tenantId=1146029695717560320, journalId=1189987059142926344, articleId=1200394758871970295, language=CN, label=表4, caption=

动态抗扰性能指标

, figureFileSmall=null, figureFileBig=null, tableContent=
控制
方式
负载转矩增加 负载转矩减少
动态
速降/
(r·min-1
稳态
误差/
(r·min-1
恢复
时间
/ms
动态
速升/
(r·min-1
稳态
误差/
(r·min-1
恢复
时间/ms
VCPERL 5.05 0.07 5.7 1.67 0.07 4.3
QPRL 5.3 0.15 10.3 2.67 0.22 7.1
DPRL 5.1 0.15 6.1 1.68 0.21 4.8
PI 5.25 0.02 15.5 1.99 0.11 12.6
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一种基于新型滑模趋近律的异步电机调速方法
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张蕊 1 , 夏岩 1 , 黄桂平 1 , 陈仁钊 2 , 杨屹立 2
电气传动 | 电气传动及其控制 2025,55(3): 13-20
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电气传动 | 电气传动及其控制 2025, 55(3): 13-20
一种基于新型滑模趋近律的异步电机调速方法
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张蕊1 , 夏岩1, 黄桂平1, 陈仁钊2, 杨屹立2
作者信息
  • 1 四川轻化工大学 自动化与信息工程学院,四川 自贡 643000
  • 2 兴储世纪科技股份有限公司,四川 自贡 643000
  • 张蕊(1998—),男,硕士,主要研究方向为电力电子传动,Email:

An Asynchronous Motor Speed Regulation Method Based on a New Sliding Mode Reaching Law
Rui ZHANG1 , Yan XIA1, Guiping HUANG1, Renzhao CHEN2, Yili YANG2
Affiliations
  • 1 School of Automation and Information Engineering,Sichuan University of Science & Engineering,Zigong 643000,Sichuan,China
  • 2 Zonergy,Zigong 643000,Sichuan,China
出版时间: 2025-03-20 doi: 10.19457/j.1001-2095.dqcd25362
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针对异步电机在传统滑模控制下的鲁棒性差和系统抖振问题,提出一种控制系数根据滑模面位置而动态变化的变系数幂指趋近律(VCPERL),并基于该趋近律设计滑模控制器。首先,考虑快速幂次趋近律(QPRL)和双幂次趋近律(DPRL)在滑模面不同位置趋近速率不同的优点,利用双曲正切函数tanh(x)替换符号函数sign(x),并在趋近律中引入变系数项,提出VCPERL。其次,根据理论分析和仿真,证明新型趋近律的稳定性。最后,根据转子磁链定向矢量控制理论和异步电机的动态数学模型,应用VCPERL设计滑模控制器。仿真结果表明,与传统PI控制、QPRL和DPRL相比,VCPERL对负载扰动具有强抗扰能力和快速恢复能力,可有效提高系统的动态响应性能。

异步电机  /  新型趋近律  /  滑模控制器  /  收敛速度  /  抗扰性能  /  动态响应

Aiming at the poor robustness and system vibration problem of asynchronous motors under the traditional sliding mode control,a variability coefficient power exponent reaching law (VCPERL) was proposed to dynamically change the control coefficients according to the position of the sliding mode surface,and the sliding mode controller was designed based on this reaching law. Firstly,according to the advantages of quick-power reaching law (QPRL) and the double-power reaching law (DPRL),which have different reaching rates at different positions of the sliding mode surface,meanwhile,the tanh(x)was used to replace the sign(x),and a variable coefficient was introduced into the reaching law. Secondly,the stability of the new reaching law was proved based on theoretical analysis and simulation. Finally,the VCPERL was applied to design the sliding mode controller according to the theory of vector control oriented by rotor magnetic chain and the dynamic mathematical model of asynchronous motor. The simulation results show that compared with the traditional PI control,QPRL and DPRL,VCPERL has strong immunity to load disturbances and fast recovery capability,which can effectively improve the dynamic response performance of the system.

asynchronous motors  /  new reaching law  /  sliding mode controller  /  convergence speed  /  disturbance carrying performance  /  dynamic response
张蕊, 夏岩, 黄桂平, 陈仁钊, 杨屹立. 一种基于新型滑模趋近律的异步电机调速方法. 电气传动, 2025 , 55 (3) : 13 -20 . DOI: 10.19457/j.1001-2095.dqcd25362
Rui ZHANG, Yan XIA, Guiping HUANG, Renzhao CHEN, Yili YANG. An Asynchronous Motor Speed Regulation Method Based on a New Sliding Mode Reaching Law[J]. Electric Drive, 2025 , 55 (3) : 13 -20 . DOI: 10.19457/j.1001-2095.dqcd25362
异步电机因其结构简单、成本低、运行稳定等优点被广泛用于工业、国防等领域。异步电机具有非线性、强耦合、多变量等特点,难以直接对其控制。传统PI控制算法简单、易于实现,但其抗扰性较差,调节时间较长,在实际工程运用中不能实现快速恢复和抖振抑制的要求。因此,为提高系统的抗扰性能、缩短调节时间和减小抖振问题,诸多学者研究出了各种解决方案,如自适应控制[1-2]、神经网络控制[3-4]和滑模控制(sliding mode control,SMC)[5-6]等,其中,SMC具有抗扰性和鲁棒性强以及响应速度快等特点,在异步电机控制系统中得到广泛研究与应用。
抖振是SMC中一个主要的问题,抖振不仅会破坏系统的稳定性,还会严重影响其实际应用。诸多学者提出各种方法来加快趋近速度并减少抖振,如边界层法[7-8]、高阶SMC[9-10]和趋近律方法等控制策略。其中,趋近律方法不仅能有效减少抖振问题,还能提高趋近速度。常见趋近律有等速趋近律[11]、指数趋近律[12-13]和幂次趋近律三种形式。在这些方法的基础上,诸多学者深入研究并改进。文献[14]提出改进指数趋近律,它能提高收敛速度并减少抖振。指数趋近律在系统远离滑模面时,能够加快趋近滑模面的速度,但趋近滑模面时,难以控制,易穿越滑模面,加剧抖振。文献[15]设计了一种快速多幂次趋近律,提高了幂次趋近律的效率,减少了抖振问题。文献[16]使用了双幂次趋近律,进一步提高了幂次趋近律的效率。文献[17-18]提出了一种改进的双幂次趋近律,可加快趋近律收敛速度并减少抖振。一般来说,幂次趋近律具有出色的趋近速度和抖振抑制效果,但在远离滑模面时,趋近滑模面较慢,延长了系统调节时间。
为了进一步提高异步电机驱动系统稳定性并减少系统抖振,本文提出一种变系数幂指趋近律(variability coefficient power exponent reaching law,VCPERL),该趋近律结合快速幂次趋近律(quick-power reaching law,QPRL)和双幂次趋近律(double-power reaching law,DPRL)在滑模面不同位置趋近速度的优点,同时用双曲正切函数tanh(x)替换符号函数sign(x),使得趋近律平滑趋近滑模面,减少抖振。为了解决幂指趋近律远离滑模面时趋近速度慢的问题,在趋近律中引入变系数项,保证系统状态能在有限时间收敛至滑模面。根据异步电机动态数学模型,应用所提趋近律设计异步电机滑模控制器,以提高系统的跟踪性能、收敛速度和抗干扰能力,削弱系统抖振。
按转子磁链定向矢量控制理论,若令旋转正交坐标系的d轴与转子磁链矢量重合,则有${\Psi }_{\mathrm{r}d}={\mathit{\Psi }}_{\mathrm{r}}$${\Psi }_{\mathrm{r}q}=0$。因此,异步电机在同步旋转正交坐标系中的状态方程为
$\left\{\begin{array}{l}\mathrm{d}\omega /\mathrm{d}t={p}^{2}{L}_{\mathrm{m}}/\left(J{L}_{\mathrm{r}}\right)·{i}_{\mathrm{s}q}{\mathit{\Psi }}_{\mathrm{r}}-p/J·{T}_{\mathrm{L}}\\ \mathrm{d}{\mathit{\Psi }}_{\mathrm{r}}/\mathrm{d}t=-1/{T}_{\mathrm{r}}·{\mathit{\Psi }}_{\mathrm{r}}+{L}_{\mathrm{m}}/{T}_{\mathrm{r}}·{i}_{\mathrm{s}d}\\ \mathrm{d}{i}_{\mathrm{s}d}/\mathrm{d}t=a/{T}_{\mathrm{r}}·{\mathit{\Psi }}_{\mathrm{r}}-b{i}_{\mathrm{s}d}+{\omega }_{1}{i}_{\mathrm{s}q}+c{u}_{\mathrm{s}d}\\ \mathrm{d}{i}_{\mathrm{s}q}/\mathrm{d}t=-a\omega {\mathit{\Psi }}_{\mathrm{r}}-b{i}_{\mathrm{s}q}-\omega {i}_{\mathrm{s}d}+c{u}_{\mathrm{s}q}\end{array}\right.$
其中

Tr=Lr/Rr

a=Lm/σLsLr

$b=({R}_{\mathrm{s}}{L}_{\mathrm{r}}^{2}+{R}_{\mathrm{r}}{L}_{\mathrm{m}}^{2})/\sigma {L}_{\mathrm{s}}{L}_{\mathrm{r}}^{2}$

c=1/σLs

$\sigma =1-{L}_{\mathrm{m}}^{2}/{L}_{\mathrm{s}}{L}_{\mathrm{r}}$

式中:Tr为转子电磁时间常数;σ为电机漏磁系数;isdisqusdusq分别为定子侧电流、电压在dq轴上的分量;RsLsRrLr分别为电机定、转子侧电阻和电感;Lm为定子与转子绕组间的互感;${\mathit{\Psi }}_{\mathrm{r}}$为转子磁链;ω为转子转速;ω1为同步旋转坐标系的旋转角速度;p为电机磁极对数;J为电机转动惯量;TL为负载转矩。
诸多学者已研究有效方法用于消除滑模控制中的抖振问题,其中,改进滑模控制的趋近律不仅可以消除抖振,还可以使系统快速趋近滑模面,例如快速幂次趋近律(QPRL)和双幂次趋近律(DPRL)。
快速幂次趋近律、双幂次趋近律表达式分别为[15]
$\dot{s}=-{k}_{1}\left|s\right.{|}^{{w}_{1}}\mathrm{s}\mathrm{i}\mathrm{g}\mathrm{n}\left(s\right)-{k}_{2}s$
$\dot{s}=-{k}_{1}\left|s\right.{|}^{{w}_{1}}\mathrm{s}\mathrm{i}\mathrm{g}\mathrm{n}\left(s\right)-{k}_{2}\left|s\right.{|}^{{w}_{2}}\mathrm{s}\mathrm{i}\mathrm{g}\mathrm{n}\left(s\right)$
其中

k1>0 k2>0

0<w1<1 w2>1

式中:s为滑模切换面函数。
符号函数sign(x)的表达式为
$\operatorname{sign}(x)=\left\{\begin{array}{ll} 1 & x>0 \\ 0 & x=0 \\ -1 & x<0 \end{array}\right.$
分析两种趋近律可知,当系统远离滑模面时,即$\left|s\right|\ge 1$,DPRL的收敛速度优于QPRL的收敛速度;反之,系统接近滑模面时,即$\left|s\right|<1$,DPRL的收敛速度慢于QPRL的收敛速度。对于DPRL,当系统接近滑模面时,趋近律的第一项幂次函数起主要作用,使系统缓慢接近滑模面;当系统远离滑模面,趋近律的第二项幂次函数起主要作用,使系统快速接近滑模面。本文将QPRL和DPRL的优点结合,提出一种新的变系数幂指趋近律(VCPERL):
$\dot{s}=-{k}_{1}f\left(s\right)\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{h}\left(\frac{s}{g}\right)-{k}_{2}\left|s\right.{|}^{{w}_{2}}\mathrm{s}\mathrm{i}\mathrm{g}\mathrm{n}\left(s\right)$
其中

$f\left(s\right)=\frac{1}{{k}_{3}+(1-{k}_{3}){\mathrm{e}}^{-h(\left|s\right|-1)}}$

k1>0 k2>0 0<k3<1

0<g<1 0<h<1 ${w}_{2}\ge 1$

k1w2为变系数,取值如下:
${k}_{1}=\left\{\begin{array}{c}{k}_{1}\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\left|s\right|\le 1\\ 2{k}_{1}\mathrm{ }\mathrm{ }\mathrm{ }\left|s\right|>1\end{array}\right.$
${w}_{2}=\left\{\begin{array}{c}1\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\left|s\right|\le 1\\ {w}_{2}\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\left|s\right|>1\end{array}\right.$
系统在滑模面不同位置时,选取不同系数,不仅提高了滑模收敛速度,而且可以抑制抖振。
根据李雅普诺夫(Lyapunov)稳定性判定依据,构造Lyapunov函数:
$V\left(x\right)={s}^{2}/2      s\ne 0$
$\dot{V}\left(x\right)<0$,可以证明反馈系统是趋于稳定的。
将VCPERL(式(5))代入式(8)中,并对其求导,可得:
$\begin{aligned} \frac{\mathrm{d}V}{\mathrm{d}t} & =-[\frac{k_{_{1}}}{k_{_{3}}+(1-k_{_{3}})\mathrm{e}^{-h(|s|-1)}}\tanh(s/g)+ \\ k_{_{2}} & \mid s\mid^{w_{_{2}}}\mathrm{sign}(s)]s \end{aligned}$
分析式(9)可知,0<k3<1,0<1-k3<1,k1>0,k2>0,第一、二项中指数函数值均大于0,双曲正切函数tanh(s/g)、符号函数sign(s)与s的正负性一致,当$s\ne 0$时,$\dot{V}\left(x\right)<0$。因此,VCPERL是渐稳定的,在有限时间内滑模面和趋近律将收敛至平衡点。
VCPERL将符号函数sign(s)替代为双曲正切函数tanh(s)。图1所示为双曲正切函数tanh(s)与符号函数sign(s)输出对比,可以看出,符号函数sign(s)输出在[-1,0,1]阶跃突变,而双曲正切函数tanh(s)输出在(-1,1)之间平滑变化。当系统远离滑模面,即$\left|s\right|>1$,VCPERL函数值趋近${k}_{1}/{k}_{3}+{k}_{2}{\left|s\right|}^{{w}_{1}}$,其中幂函数随着s的变化而动态变化,减小系统趋近抖振,比例系数和幂函数的结合增加系统趋近滑模面的速度。当系统状态趋近于0时,即$\left|s\right|\to 0$,双曲正切函数tanh(s)平滑趋近于0,VCPERL函数值随着s变化而趋近于0,实现抖振抑制。综上所述,VCPERL的两部分可以根据s的大小而动态变化,不仅提高系统趋近滑模面的速度,而且实现滑模控制抖振的抑制。
VCPERL具有响应快、自适应强、稳定的特点,为了验证VCPERL的特性,分别将VCPERL,QPRL及DPRL在Matlab/Simulink平台搭建典型单输入单输出系统(single input single output,SISO)仿真模型。
典型SISO系统如下式 :
$\dot{\mathit{X}}=\mathit{A}\mathit{X}+\mathit{B}u$
其中

$\mathit{X}=\left[\begin{array}{c}{x}_{1}\\ {x}_{2}\end{array}\right]$$\mathit{A}=\left[\begin{array}{cc}0& 1\\ 0& 0\end{array}\right]$$\mathit{B}=\left[\begin{array}{c}0\\ 5\mathrm{ }000\end{array}\right]$

系统滑模面为

s=CX

其中

$\mathit{C}=\left[\begin{array}{cc}1& 1\end{array}\right]$

式中:X为系统状态变量;AB为参数矩阵;C为滑模面系数;u为系统控制量。
假设系统无扰动,趋近律参数如表1所示。
与QPRL,DPRL相比,VCPERL控制系统最早趋近滑模面,仿真结果如图2a图2b所示。控制器输出和状态变量最快收敛至平衡点,仿真如图2c图2d所示。VCPERL在趋近速度、系统收敛时间都更有优势。
首先定义磁链、转速误差:
$\mathit{e}=\left[\begin{array}{c}{e}_{\Psi }\\ {e}_{\omega }\end{array}\right]=\left[\begin{array}{c}{\mathit{\Psi }}_{\mathrm{r}}^{\mathrm{*}}-{\mathit{\Psi }}_{\mathrm{r}}\\ {\omega }^{\mathrm{*}}-\omega \end{array}\right]$
式中:${\mathit{\Psi }}_{\mathrm{r}}^{\mathrm{*}}$ω*分别为给定磁链、转速;${\mathit{\Psi }}_{\mathrm{r}}$,ω分别为反馈磁链、转速。
定义磁链、速度滑模面为
$\mathit{s}=\left[\begin{array}{c}{s}_{\Psi }\\ {s}_{\omega }\end{array}\right]=\left[\begin{array}{c}{e}_{\Psi }\\ {e}_{\omega }\end{array}\right]$
对式(13)进行微分运算,可得:
$\dot{\mathit{s}}=\left[\begin{array}{c}{\dot{s}}_{\Psi }\\ {\dot{s}}_{\omega }\end{array}\right]=\left[\begin{array}{c}{\dot{e}}_{\Psi }\\ {\dot{e}}_{\omega }\end{array}\right]$
将VCPERL与式(1)中转速状态方程和磁链状态方程代入式(14)中,可得:
$\begin{array}{l}-\left[\begin{array}{c}{k}_{1\Psi }f\left({s}_{\Psi }\right)\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{h}\left(\frac{{s}_{\Psi }}{{g}_{\Psi }}\right)+{k}_{2\Psi }\left|{s}_{\Psi }{|}^{{w}_{2\Psi }}\mathrm{s}\mathrm{i}\mathrm{g}\mathrm{n}\right({s}_{\Psi })\\ {k}_{1\omega }f\left({s}_{\omega }\right)\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{h}\left(\frac{{s}_{\omega }}{{g}_{\omega }}\right)+{k}_{2\omega }\left|{s}_{\omega }{|}^{{w}_{2\omega }}\mathrm{s}\mathrm{i}\mathrm{g}\mathrm{n}\right({s}_{\omega })\end{array}\right]=\left[\begin{array}{c}{\dot{\mathit{\Psi }}}_{\mathrm{r}}^{\mathrm{*}}\\ {\dot{\omega }}^{\mathrm{*}}\end{array}\right]+\\ \mathrm{ }\mathrm{ }\mathrm{ }\left[\begin{array}{c}\frac{{\mathit{\Psi }}_{\mathrm{r}}}{{T}_{\mathrm{r}}}-\frac{L}{{T}_{\mathrm{r}}}{i}_{\mathrm{s}d}\\ -\frac{{p}^{2}{L}_{\mathrm{m}}}{J{L}_{\mathrm{r}}}{i}_{\mathrm{s}q}{\mathit{\Psi }}_{\mathrm{r}}+\frac{p}{J}{T}_{\mathrm{L}}\end{array}\right]\end{array}$
整理式(15)可得到速度、磁链滑模控制律:
$\left[\begin{array}{c}{i}_{\mathrm{s}d}\\ {i}_{\mathrm{s}q}\end{array}\right]=\left[\begin{array}{c}{k}_{4}\\ {k}_{5}\end{array}\right]\{\left[\begin{array}{c}\frac{{\mathit{\Psi }}_{\mathrm{r}}}{{T}_{\mathrm{r}}}\\ \frac{p}{J}{T}_{\mathrm{L}}\end{array}\right]+\left[\begin{array}{c}{k}_{1\Psi }\\ {k}_{1\omega }\end{array}\right]\left[\begin{array}{c}f\left({s}_{\Psi }\right)\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{h}\left(\frac{{s}_{\Psi }}{{g}_{\Psi }}\right)\\ f\left({s}_{\omega }\right)\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{h}\left(\frac{{s}_{\omega }}{{g}_{\omega }}\right)\end{array}\right]+\left[\begin{array}{c}{k}_{2\Psi }\\ {k}_{2\omega }\end{array}\right]\left[\begin{array}{c}{\left|{s}_{\Psi }\right|}^{{w}_{2\Psi }}\mathrm{s}\mathrm{i}\mathrm{g}\mathrm{n}\left({s}_{\Psi }\right)\\ {\left|{s}_{\omega }\right|}^{{w}_{2\omega }}\mathrm{s}\mathrm{i}\mathrm{g}\mathrm{n}\left({s}_{\omega }\right)\end{array}\right]+\left[\begin{array}{c}{\dot{\mathit{\Psi }}}_{\mathrm{r}}^{\mathrm{*}}\\ {\dot{\omega }}^{\mathrm{*}}\end{array}\right]$}
其中

k4=Tr/Lm

${k}_{5}=J{L}_{\mathrm{r}}/{p}^{2}{L}_{\mathrm{m}}{\mathit{\Psi }}_{\mathrm{r}}$

首先定义定子电流dq轴分量误差:
${\mathit{e}}_{i}=\left[\begin{array}{c}{e}_{{i}_{\mathrm{s}d}}\\ {e}_{{i}_{\mathrm{s}q}}\end{array}\right]=\left[\begin{array}{c}{i}_{\mathrm{s}d}^{\mathrm{*}}-{i}_{\mathrm{s}d}\\ {i}_{\mathrm{s}q}^{\mathrm{*}}-{i}_{\mathrm{s}q}\end{array}\right]$
式中:${i}_{\mathrm{s}d}^{\mathrm{*}}$${i}_{\mathrm{s}q}^{\mathrm{*}}$分别为磁链控制器、速度控制器的输出电流;isdisq分别为反馈dq轴电流。
定义dq轴电流滑模面为
${\mathit{s}}_{i}=\left[\begin{array}{c}{s}_{{i}_{\mathrm{s}d}}\\ {s}_{{i}_{\mathrm{s}q}}\end{array}\right]=\left[\begin{array}{c}{e}_{{i}_{\mathrm{s}d}}\\ {e}_{{i}_{\mathrm{s}q}}\end{array}\right]$
对式(18)进行微分运算,可得:
${\dot{\mathit{s}}}_{i}=\left[\begin{array}{c}{\dot{s}}_{{i}_{\mathrm{s}d}}\\ {\dot{s}}_{{i}_{\mathrm{s}q}}\end{array}\right]=\left[\begin{array}{c}{\dot{e}}_{{i}_{\mathrm{s}d}}\\ {\dot{e}}_{{i}_{\mathrm{s}q}}\end{array}\right]$
将VCPERL与式(1)中dq电流状态方程代入式(19)中,可得:
$\begin{array}{l}-\left[\begin{array}{c}{k}_{1{i}_{\mathrm{s}d}}f\left({s}_{{i}_{\mathrm{s}d}}\right)\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{h}\left(\frac{{s}_{{i}_{\mathrm{s}d}}}{{g}_{{i}_{\mathrm{s}d}}}\right)+{k}_{2{i}_{\mathrm{s}d}}\left|{s}_{{i}_{\mathrm{s}d}}{|}^{{w}_{2{i}_{\mathrm{s}d}}}\mathrm{s}\mathrm{i}\mathrm{g}\mathrm{n}\right({s}_{{i}_{\mathrm{s}d}})\\ {k}_{1{i}_{\mathrm{s}q}}f\left({s}_{{i}_{\mathrm{s}q}}\right)\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{h}\left(\frac{{s}_{{i}_{\mathrm{s}q}}}{{g}_{{i}_{\mathrm{s}q}}}\right)+{k}_{2{i}_{\mathrm{s}q}}\left|{s}_{{i}_{\mathrm{s}q}}{|}^{{w}_{2{i}_{\mathrm{s}q}}}\mathrm{s}\mathrm{i}\mathrm{g}\mathrm{n}\right({s}_{{i}_{\mathrm{s}q}})\end{array}\right]=\left[\begin{array}{c}{\dot{i}}_{\mathrm{s}d}^{\mathrm{*}}\\ {\dot{i}}_{\mathrm{s}q}^{\mathrm{*}}\end{array}\right]+\\ \mathrm{ }\mathrm{ }\mathrm{ }\left[\begin{array}{c}-\frac{a}{{T}_{\mathrm{r}}}{\mathit{\Psi }}_{\mathrm{r}}+b{i}_{\mathrm{s}d}-{\omega }_{1}{i}_{\mathrm{s}q}-c{u}_{\mathrm{s}d}\\ a\omega {\mathit{\Psi }}_{\mathrm{r}}+b{i}_{\mathrm{s}q}+\omega {i}_{\mathrm{s}d}-c{u}_{\mathrm{s}q}\end{array}\right]\end{array}$
整理式(20)可得dq轴电流滑模控制律:
$\begin{array}{l}\left[\begin{array}{c}{u}_{\mathrm{s}d}\\ {u}_{\mathrm{s}q}\end{array}\right]=\sigma {L}_{\mathrm{s}}\{\left[\begin{array}{c}{k}_{1{i}_{\mathrm{s}d}}\\ {k}_{1{i}_{\mathrm{s}q}}\end{array}\right]\left[\begin{array}{c}f\left({s}_{{i}_{\mathrm{s}d}}\right)\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{h}\left(\frac{{s}_{{i}_{\mathrm{s}d}}}{{g}_{{i}_{\mathrm{s}d}}}\right)\\ f\left({s}_{{i}_{\mathrm{s}q}}\right)\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{h}\left(\frac{{s}_{{i}_{\mathrm{s}q}}}{{g}_{{i}_{\mathrm{s}q}}}\right)\end{array}\right]+\\ \left[\begin{array}{c}{k}_{2{i}_{\mathrm{s}d}}\\ {k}_{2{i}_{\mathrm{s}q}}\end{array}\right]\left[\begin{array}{c}{\left|{s}_{{i}_{\mathrm{s}d}}\right|}^{{w}_{2{i}_{\mathrm{s}d}}}\mathrm{s}\mathrm{i}\mathrm{g}\mathrm{n}\left({s}_{{i}_{\mathrm{s}d}}\right)\\ {\left|{s}_{{i}_{\mathrm{s}q}}\right|}^{{w}_{2{i}_{\mathrm{s}q}}}\mathrm{s}\mathrm{i}\mathrm{g}\mathrm{n}\left({s}_{{i}_{\mathrm{s}q}}\right)\end{array}\right]+\\ \left[\begin{array}{c}-\frac{a}{{T}_{\mathrm{r}}}{\mathit{\Psi }}_{\mathrm{r}}+b{i}_{\mathrm{s}d}-{\omega }_{1}{i}_{\mathrm{s}q}-c{u}_{\mathrm{s}d}\\ a\omega {\mathit{\Psi }}_{\mathrm{r}}+b{i}_{\mathrm{s}q}+\omega {i}_{\mathrm{s}d}-c{u}_{\mathrm{s}q}\end{array}\right]+\left[\begin{array}{c}{\dot{i}}_{\mathrm{s}d}^{\mathrm{*}}\\ {\dot{i}}_{\mathrm{s}q}^{\mathrm{*}}\end{array}\right]\}\end{array}$
为验证本文提出的VCPERL抑制抖振、抗干扰和快速响应的效果,分别将VCPERL,QPRL,DPRL和PI控制在Matlab/Simulink平台中搭建转子磁链定向矢量控制的异步电机控制系统,进行仿真,对仿真结果进行对比分析。控制系统的直流侧电压为600 V,逆变器开关频率设定为10 kHz,被控异步电机参数为:额定功率Pn=2.2 kW,额定电压Un=380 V,额定频率fn=50 Hz,定子电阻Rs=2.88 Ω,定子电感Ls=0.016 H,转子电阻Rr=2.586 Ω,转子电感Lr=0.016 H,互感Lm=0.349 H,极对数p=3,转动惯量J=0.028 5 kg·m2。系统控制结构图如图3所示。
为了比较趋近律的控制效果,三种趋近律公有参数数值一致,三种趋近律参数如表2所示。
系统动态跟随性能仿真给定转速800 r/min,给定负载转矩10 N·m。动态跟随性能仿真的转速波形如图4所示,动态跟随性能指标如表3所示。由转速波形对比分析可知,VCPERL滑模控制系统上升时间为75 ms,调节时间为81 ms,稳态误差为0.07 r/min,调节时间最短,趋近速度最快,动态跟随性能指标明显优于其他趋近律和PI控制。
动态跟随性能仿真的电磁转矩波形如图5所示。由电磁转矩波形分析可知,启动阶段,滑模控制系统与PI控制系统相比,滑模控制系统的电磁转矩上升速度快;调节阶段,滑模控制系统的电磁转矩系统波动幅度小、调节次数少,其中,VCPERL滑模控制系统的电磁转矩波动幅值为3 N·m,波动幅度小;稳定阶段,VCPERL的电磁转矩输出最平稳、无波动。
动态跟随性能仿真的dq轴电流波形如图6图7所示。分析可知,调节阶段,PI控制系统的dq轴电流振荡最大幅值为3.8 A,16.3 A;QPRL滑模控制系统的dq轴电流振荡最大幅值为2 A,9.6 A;DPRL的dq轴电流振荡最大幅值为8.2 A,12.5 A;VCPERL的dq轴电流振荡最大幅值为2.2 A,10 A。VCPERL的dq轴电流振荡幅值最小,调节次数为1次。稳定阶段,QPRL和DPRL的dq轴电流无规律振荡,变化频率快;VCPERL的dq轴电流较平稳,振荡幅值为0.06 A,0.2 A,振荡幅值最小,且呈现有规律振荡。
系统动态抗扰性能仿真给定转速800 r/min,给定负载转矩初始值为10 N·m;在0.5 s时,负载转矩阶跃至25 N·m;在1 s时,负载转矩骤降至5 N·m。动态抗扰性能仿真的转速波形如图8所示。动态跟随性能指标如表4所示。由转速波形结果对比分析可知,当负载转矩由10 N·m阶跃至25 N·m时,与PI控制相比,滑模控制系统的动态速降较小,系统稳态恢复时间短,其中,VCPERL的动态速降为5.05 r/min,稳态恢复时间为5.7 ms,稳态误差为0.07 r/min。当负载转矩由25 N·m骤降至5 N·m时,VCPERL的动态速升为1.67 r/min,稳态恢复时间为4.3 ms,稳态误差为0.07 r/min。负载转矩无论是增大还是减小,VCPERL滑模控制的转速变化、稳态恢复时间和稳态误差都是三种趋近律中控制效果最好的。因此,VCPERL滑模控制具有抗干扰、稳定性好的特点。
动态抗扰性能仿真的电磁转矩波形如图9所示。当负载转矩发生突变时,滑模控制系统响应速度快,电机输出的电磁转矩能够跟踪负载转矩的动态变化。在稳态阶段,VCPERL滑模控制的电磁转矩振荡幅值最小、稳定性最佳。
动态抗扰性能仿真的d轴电流波形如图10所示;负载转矩由10 N·m阶跃至25 N·m时的d轴电流如图11所示;负载转矩由25 N·m骤降至5 N·m时的d轴电流如图12所示。
负载转矩发生突变时,滑模控制系统的d轴电流几乎无波动。当负载转矩由10 N·m阶跃至25 N·m时,VCPERL滑模控制的d轴电流振荡幅值为0.175 A,恢复时间5 ms。QPRL,DPRL和PI控制系统的d轴电流振荡幅值分别为0.178 A,0.275 A和2.25 A。当负载转矩由25 N·m骤降至5 N·m时,VCPERL滑模控制系统的d轴电流振荡幅值为0.275 A,7 ms后恢复。QPRL,DPRL和PI控制系统的d轴电流振荡幅值分别为0.25 A,0.275 A和1.75 A。虽然VCPERL的电流振荡幅值略大于QPRL,但VCPERL的电流尖峰和谐波含量少,且稳态恢复时间较短。
动态抗扰性能仿真的q轴电流波形如图13所示;负载转矩由10 N·m阶跃至25 N·m的q轴电流如图14所示;负载转矩由25 N·m骤降至5 N·m时的q轴电流如图15所示。当负载转矩发生突变时,VCPERL滑模控制系统q轴电流的稳态调节时间最短、振荡幅值最小。系统进入稳态时,VCPERL滑模控制系统的q轴电流几乎无波动。
为了削弱异步电机调速系统抖振和鲁棒性差的问题,提出一种根据滑模面位置而动态变化的变系数幂指趋近律,并得出如下结论:
1)将幂函数和指数函数结合,可有效抑制系统抖振。在趋近律中引入变系数项,可有效加快趋近律在远离滑模面时的趋近速度。
2)利用双曲正切函数tanh(x)替换符号函数sign(x),可使趋近律平滑趋近滑模面,进一步减小系统抖振。
3)根据Lyapunov函数证明VCPERL的稳定性,并利用该趋近律设计了滑模控制器。
仿真结果表明,在动态跟随性能方面,VCPERL系统的转速稳态误差由PI控制的0.13 r/min,QPRL的0.16 r/min和DPRL的0.19 r/min降至0.07 r/min。稳态调节时间缩短至81 ms。在动态抗扰性能方面,当负载转矩较大变化时(低于额定转矩的120%),VCPERL系统能够在短时间内恢复至稳态,与QPRL,DPRL和PI控制相比,VCPERL转速变化最小、稳态恢复时间最短、调节次数最少。验证了VCPERL能够有效削弱滑模系统抖振、加快系统的响应速度、增强系统的鲁棒性。
  • 智能电网四川省重点实验室(2022-IEPGKLSP-KFYB05)
  • 四川省科技计划资助(2022SZYZF01)
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2025年第55卷第3期
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doi: 10.19457/j.1001-2095.dqcd25362
  • 接收时间:2023-09-06
  • 首发时间:2025-11-26
  • 出版时间:2025-03-20
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  • 收稿日期:2023-09-06
  • 修回日期:2023-11-13
基金
智能电网四川省重点实验室(2022-IEPGKLSP-KFYB05)
四川省科技计划资助(2022SZYZF01)
作者信息
    1 四川轻化工大学 自动化与信息工程学院,四川 自贡 643000
    2 兴储世纪科技股份有限公司,四川 自贡 643000
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