{"title":"Vector control of permanent magnet synchronous motor drive system based on new sliding mode control","authors":"Yun Zhang, Hao Wu, Ying-Ren Chien, Jingwei Tang","doi":"10.1587/elex.20.20230263","DOIUrl":null,"url":null,"abstract":"A new sliding mode speed controller (NSMC) based on an improved genetic algorithm (IGA) is proposed to solve the problems of disturbance rejection and response speed differences in traditional vector control of permanent magnet synchronous motor (PMSM) driver systems. The improved algorithm adopts an adaptive crossover and mutation probability formula, which enhances the global search ability of the genetic algorithm. The algorithm is used to optimize the parameters of the sliding mode speed controller. Moreover, the sliding mode disturbance observer is used to generate feedforward signals to compensate for the influence of external disturbances. It is applied to the speed control loop to effectively improve the system’s robustness. Finally, numerical simulation results demonstrate the robustness and fast response of the proposed method.","PeriodicalId":50387,"journal":{"name":"Ieice Electronics Express","volume":null,"pages":null},"PeriodicalIF":0.8000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ieice Electronics Express","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1587/elex.20.20230263","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
A new sliding mode speed controller (NSMC) based on an improved genetic algorithm (IGA) is proposed to solve the problems of disturbance rejection and response speed differences in traditional vector control of permanent magnet synchronous motor (PMSM) driver systems. The improved algorithm adopts an adaptive crossover and mutation probability formula, which enhances the global search ability of the genetic algorithm. The algorithm is used to optimize the parameters of the sliding mode speed controller. Moreover, the sliding mode disturbance observer is used to generate feedforward signals to compensate for the influence of external disturbances. It is applied to the speed control loop to effectively improve the system’s robustness. Finally, numerical simulation results demonstrate the robustness and fast response of the proposed method.
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