{"title":"Improved predictive current control by parameter estimation in grid connected inverter applications","authors":"Yohan Baek, Kui-Jun Lee, D. Hyun","doi":"10.1109/IPEMC.2009.5157632","DOIUrl":null,"url":null,"abstract":"An improved predictive current control through parameter estimation is presented. The future value of grid current is predicted by a discrete-time model. The predicted value of grid current is evaluated by the quality function. The optimal switching state that minimizes the quality function is selected. The predictive current control is sensitive to variations in parameters. The effect of variations in parameter values on control system is compensated by parameter estimation. The parameter estimation is achieved by the least square method. The estimated parameters are applied to predictive model and it improves an accuracy of control system.","PeriodicalId":375971,"journal":{"name":"2009 IEEE 6th International Power Electronics and Motion Control Conference","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2009-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE 6th International Power Electronics and Motion Control Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPEMC.2009.5157632","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
An improved predictive current control through parameter estimation is presented. The future value of grid current is predicted by a discrete-time model. The predicted value of grid current is evaluated by the quality function. The optimal switching state that minimizes the quality function is selected. The predictive current control is sensitive to variations in parameters. The effect of variations in parameter values on control system is compensated by parameter estimation. The parameter estimation is achieved by the least square method. The estimated parameters are applied to predictive model and it improves an accuracy of control system.
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