Naithan Peter, Nitendran Maniam, H. Mudaliar, M. Cirrincione, Ravneel Prasad, S. Chand, A. Fagiolini
{"title":"Adaptive Field-Oriented Control of Permanent Magnet Synchronous Motor Using Feedfoward Actions","authors":"Naithan Peter, Nitendran Maniam, H. Mudaliar, M. Cirrincione, Ravneel Prasad, S. Chand, A. Fagiolini","doi":"10.1109/IC_ASET58101.2023.10150634","DOIUrl":null,"url":null,"abstract":"This paper proposes a method for estimating the mechanical parameters of a Permanent Magnet Synchronous Motor (PMSM) using the Forgetting Factor Recursive Least Squares (RLS) algorithm. The estimated parameters are used to perform adaptive feedforward control actions, as the mechanical parameters of a PMSM tend to change with varying loads and speed. The simulation of the proposed technique is carried out using MATLAB/Simulink® under different conditions. The results demonstrate the accuracy of the technique in estimating the mechanical parameters and enhancing the performance of the drive. The proposed technique offers a promising solution to control PMSMs under dynamic conditions and can be useful in various industrial applications. The methodology, simulation setup, and results are presented in this paper.","PeriodicalId":272261,"journal":{"name":"2023 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC_ASET58101.2023.10150634","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper proposes a method for estimating the mechanical parameters of a Permanent Magnet Synchronous Motor (PMSM) using the Forgetting Factor Recursive Least Squares (RLS) algorithm. The estimated parameters are used to perform adaptive feedforward control actions, as the mechanical parameters of a PMSM tend to change with varying loads and speed. The simulation of the proposed technique is carried out using MATLAB/Simulink® under different conditions. The results demonstrate the accuracy of the technique in estimating the mechanical parameters and enhancing the performance of the drive. The proposed technique offers a promising solution to control PMSMs under dynamic conditions and can be useful in various industrial applications. The methodology, simulation setup, and results are presented in this paper.