{"title":"Load torque observation and compensation for permanent magnet synchronous motor based on sliding mode observer","authors":"Zenghui Lu, Hongjie Fan, Dong Xu","doi":"10.12688/cobot.17689.1","DOIUrl":null,"url":null,"abstract":"Background Permanent magnet synchronous motors (PMSM) are widely used in various industries. However, in practical applications, the time-varying nature of load torque may lead to speed fluctuations, negatively impacting the motor's control performance and stability. To mitigate these issues, this paper proposes a load torque observation method for PMSMs based on a sliding mode observer. Methods The sliding mode observer is designed to estimate the load torque and convert it into a current, which is fed back as a feedforward compensation to the q-axis current in the current closed-loop control system. The observer's dynamic performance is optimized using a genetic algorithm to minimize the Integral of Time-weighted Absolute Error (ITAE) between the observer and the actual system state. Experimental tests are conducted on a motor torque testing platform. After stabilizing the motor at 800rpm, a sudden torque of 0.5Nm is applied. Results Compared to the situation without load torque compensation, the motor speed fluctuations are reduced by approximately 60% after adding load torque compensation. Conclusions This enhancement improves the system's speed control performance during torque variations and increases the system's robustness and disturbance rejection capability.","PeriodicalId":29807,"journal":{"name":"Cobot","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cobot","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12688/cobot.17689.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background Permanent magnet synchronous motors (PMSM) are widely used in various industries. However, in practical applications, the time-varying nature of load torque may lead to speed fluctuations, negatively impacting the motor's control performance and stability. To mitigate these issues, this paper proposes a load torque observation method for PMSMs based on a sliding mode observer. Methods The sliding mode observer is designed to estimate the load torque and convert it into a current, which is fed back as a feedforward compensation to the q-axis current in the current closed-loop control system. The observer's dynamic performance is optimized using a genetic algorithm to minimize the Integral of Time-weighted Absolute Error (ITAE) between the observer and the actual system state. Experimental tests are conducted on a motor torque testing platform. After stabilizing the motor at 800rpm, a sudden torque of 0.5Nm is applied. Results Compared to the situation without load torque compensation, the motor speed fluctuations are reduced by approximately 60% after adding load torque compensation. Conclusions This enhancement improves the system's speed control performance during torque variations and increases the system's robustness and disturbance rejection capability.
期刊介绍:
Cobot is a rapid multidisciplinary open access publishing platform for research focused on the interdisciplinary field of collaborative robots. The aim of Cobot is to enhance knowledge and share the results of the latest innovative technologies for the technicians, researchers and experts engaged in collaborative robot research. The platform will welcome submissions in all areas of scientific and technical research related to collaborative robots, and all articles will benefit from open peer review.
The scope of Cobot includes, but is not limited to:
● Intelligent robots
● Artificial intelligence
● Human-machine collaboration and integration
● Machine vision
● Intelligent sensing
● Smart materials
● Design, development and testing of collaborative robots
● Software for cobots
● Industrial applications of cobots
● Service applications of cobots
● Medical and health applications of cobots
● Educational applications of cobots
As well as research articles and case studies, Cobot accepts a variety of article types including method articles, study protocols, software tools, systematic reviews, data notes, brief reports, and opinion articles.