Article(id=1321491464526344832, tenantId=1146029695717560320, journalId=1146031654075715584, issueId=1321491360620851250, articleNumber=null, orderNo=null, doi=10.13234/j.issn.2095-2805.2025.7.229, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1692633600000, receivedDateStr=2023-08-22, revisedDate=1701964800000, revisedDateStr=2023-12-08, acceptedDate=1703779200000, acceptedDateStr=2023-12-29, onlineDate=1792997717267, onlineDateStr=2026-10-26, pubDate=1764432000000, pubDateStr=2025-11-30, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792997717267, onlineIssueDateStr=2026-10-26, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792997717267, creator=13701087609, updateTime=1792997717267, updator=13701087609, issue=Issue{id=1321491360620851250, tenantId=1146029695717560320, journalId=1146031654075715584, year='2025', volume='23', issue='7', pageStart='1', pageEnd='348', issueExtLink='null', onlineDate='null', pubDate='1764432000000', pubDateStr='2025-11-30', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792997692494, creator='13701087609', updateTime=1792997936183, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1321492382776931282, tenantId=1146029695717560320, journalId=1146031654075715584, issueId=1321491360620851250, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1321492382776931283, tenantId=1146029695717560320, journalId=1146031654075715584, issueId=1321491360620851250, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=229, endPage=237, ext={EN=ArticleExt(id=1321491464798974593, articleId=1321491464526344832, tenantId=1146029695717560320, journalId=1146031654075715584, language=EN, title=PMSM Model Predictive Torque Control Based on Dual-sliding-mode Observer, columnId=1152281495567168372, journalTitle=Journal of Power Supply, columnName=Electric Machine System and Control, runingTitle=null, highlight=null, articleAbstract=

To address the issue that the conventional model predictive torque control algorithm for a permanent magnet synchronous motor relies on position sensors, a model predictive torque control approach based on a dualsliding-mode observer is proposed. First, to accomplish the sensorless control, the real-time speed in the prediction model is substituted by the observed speed by coupling the back electromotive force sliding-mode observer with the optimized quadrature phase-locked loop. Second, the stator flux sliding-mode observer is used to observe the stator flux, and the observed flux introduces prediction error through feedback correction to obtain the prediction torque and flux with higher accuracy, thus improving the prediction speed and accuracy of the model predictive torque control system. By contrasting the MATLAB/Simulink simulation and experimental platform with the conventional model predictive torque control approach incorporating position sensors, the efficacy and feasibility of the proposed method are confirmed.

, authors=Jichao LI, Jian LI, Binbin ZHANG, Chaobo CHEN, Song GAO, authorsList=Jichao LI, Jian LI, Binbin ZHANG, Chaobo CHEN, Song GAO, authorCompany=null, correspAuthors=Chaobo CHEN, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1321491468200555140, articleId=1321491464526344832, tenantId=1146029695717560320, journalId=1146031654075715584, language=CN, title=基于双滑模观测器的PMSM模型预测转矩控制, columnId=1149830230325616646, journalTitle=电源学报, columnName=电机系统与控制, runingTitle=null, highlight=null, articleAbstract=

为了解决永磁同步电机中传统模型预测转矩控制算法依赖位置传感器的问题,提出1种基于双滑模观测器的模型预测转矩控制方法。首先,通过将反电动势滑模观测器与优化后的正交锁相环结合,用观测转速替换预测模型中的实时转速,实现无位置传感器控制。其次,应用定子磁链滑模观测器观测定子磁链,观测磁链通过反馈校正引入预测误差以获得更准确的预测转矩和磁链,提升模型的预测速度和精度。最后,通过MATLAB/Simulink仿真和实验平台与传统含位置传感器的模型预测转矩控制方法对比,验证所提方法的有效性和可行性。

, authors=李继超, 李健, 张彬彬, 陈超波, 高嵩, authorsList=李继超, 李健, 张彬彬, 陈超波, 高嵩, authorCompany=null, correspAuthors=陈超波, authorNote=

李继超(1989— ),男,硕士,工程师。研究方向:智能控制。E-mail:。

李健(1997— ),男,硕士。研究方向:电机高性能控制。E-mail:。

张彬彬(1990— ),男,博士,讲师。研究方向:智能控制。E-mail:。

高嵩(1966— ),男,博士,教授。研究方向:智能控制与多传感器信息融合。E-mail:。

, correspAuthorsNote=
陈超波(1978— ),男,通信作者,博士,教授。研究方向:故障诊断与容错控制和智能控制。E-mail:。
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李继超(1989— ),男,硕士,工程师。研究方向:智能控制。E-mail:。

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李继超(1989— ),男,硕士,工程师。研究方向:智能控制。E-mail:。

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李健(1997— ),男,硕士。研究方向:电机高性能控制。E-mail:。

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李健(1997— ),男,硕士。研究方向:电机高性能控制。E-mail:。

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张彬彬(1990— ),男,博士,讲师。研究方向:智能控制。E-mail:。

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张彬彬(1990— ),男,博士,讲师。研究方向:智能控制。E-mail:。

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高嵩(1966— ),男,博士,教授。研究方向:智能控制与多传感器信息融合。E-mail:。

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高嵩(1966— ),男,博士,教授。研究方向:智能控制与多传感器信息融合。E-mail:。

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基于双滑模观测器的PMSM模型预测转矩控制
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李继超 , 李健 , 张彬彬 , 陈超波 , 高嵩
电源学报 | 电机系统与控制 2025,23(7): 229-237
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电源学报 |电机系统与控制 2025 , 23 (7) : 229 -237
基于双滑模观测器的PMSM模型预测转矩控制
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张彬彬(1990— ),男,博士,讲师。研究方向:智能控制。E-mail:。

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张彬彬(1990— ),男,博士,讲师。研究方向:智能控制。E-mail:。

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高嵩(1966— ),男,博士,教授。研究方向:智能控制与多传感器信息融合。E-mail:。

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李继超 , 李健 , 张彬彬 , 陈超波 , 高嵩
作者信息
  • 西安工业大学电子信息工程学院,西安 710021
通讯作者:
陈超波(1978— ),男,通信作者,博士,教授。研究方向:故障诊断与容错控制和智能控制。E-mail:。
作者简介:

李继超(1989— ),男,硕士,工程师。研究方向:智能控制。E-mail:。

李健(1997— ),男,硕士。研究方向:电机高性能控制。E-mail:。

张彬彬(1990— ),男,博士,讲师。研究方向:智能控制。E-mail:。

高嵩(1966— ),男,博士,教授。研究方向:智能控制与多传感器信息融合。E-mail:。

PMSM Model Predictive Torque Control Based on Dual-sliding-mode Observer
Jichao LI , Jian LI , Binbin ZHANG , Chaobo CHEN , Song GAO
Affiliations
  • School of Electronic Information Engineering, Xi’an Technological University, Xi’an 710021, China
出版时间: 2025-11-30 doi: 10.13234/j.issn.2095-2805.2025.7.229
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为了解决永磁同步电机中传统模型预测转矩控制算法依赖位置传感器的问题,提出1种基于双滑模观测器的模型预测转矩控制方法。首先,通过将反电动势滑模观测器与优化后的正交锁相环结合,用观测转速替换预测模型中的实时转速,实现无位置传感器控制。其次,应用定子磁链滑模观测器观测定子磁链,观测磁链通过反馈校正引入预测误差以获得更准确的预测转矩和磁链,提升模型的预测速度和精度。最后,通过MATLAB/Simulink仿真和实验平台与传统含位置传感器的模型预测转矩控制方法对比,验证所提方法的有效性和可行性。

永磁同步电机  /  模型预测转矩控制  /  无位置传感器控制  /  双滑模观测器  /  正交锁相环

To address the issue that the conventional model predictive torque control algorithm for a permanent magnet synchronous motor relies on position sensors, a model predictive torque control approach based on a dualsliding-mode observer is proposed. First, to accomplish the sensorless control, the real-time speed in the prediction model is substituted by the observed speed by coupling the back electromotive force sliding-mode observer with the optimized quadrature phase-locked loop. Second, the stator flux sliding-mode observer is used to observe the stator flux, and the observed flux introduces prediction error through feedback correction to obtain the prediction torque and flux with higher accuracy, thus improving the prediction speed and accuracy of the model predictive torque control system. By contrasting the MATLAB/Simulink simulation and experimental platform with the conventional model predictive torque control approach incorporating position sensors, the efficacy and feasibility of the proposed method are confirmed.

Permanent magnet synchronous motor  /  model predictive torque control  /  sensorless control  /  dual-sliding-mode observer  /  quadrature phase-locked loop
李继超, 李健, 张彬彬, 陈超波, 高嵩. 基于双滑模观测器的PMSM模型预测转矩控制. 电源学报, 2025 , 23 (7) : 229 -237 . DOI: 10.13234/j.issn.2095-2805.2025.7.229
Jichao LI, Jian LI, Binbin ZHANG, Chaobo CHEN, Song GAO. PMSM Model Predictive Torque Control Based on Dual-sliding-mode Observer[J]. Journal of Power Supply, 2025 , 23 (7) : 229 -237 . DOI: 10.13234/j.issn.2095-2805.2025.7.229
  • 国家重点研发计划资助项目(2022YFE0123400)
  • 陕西省技术创新引导计划项目(2022QFY01-16)
  • 西安市未央区科技计划项目(202205)
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2025年第23卷第7期
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文章信息
doi: 10.13234/j.issn.2095-2805.2025.7.229
  • 接收时间:2023-08-22
  • 首发时间:2026-10-26
  • 出版时间:2025-11-30
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出版历史
  • 收稿日期:2023-08-22
  • 修回日期:2023-12-08
  • 录用日期:2023-12-29
基金
National Key Research and Development Plan(2022YFE0123400)
国家重点研发计划资助项目(2022YFE0123400)
Technology Innovation Guidance Program of Shaanxi Province(2022QFY01-16)
陕西省技术创新引导计划项目(2022QFY01-16)
Xi’an Weiyang District Science and Technology Project(202205)
西安市未央区科技计划项目(202205)
作者信息
    西安工业大学电子信息工程学院,西安 710021

通讯作者:

陈超波(1978— ),男,通信作者,博士,教授。研究方向:故障诊断与容错控制和智能控制。E-mail:。
参考文献
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Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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