B. Bossoufi, Hala Alami Aroussi, M. E. Ghamrasni, Y. Ihedrane
{"title":"Speed control for PMSM drive system using predictive control","authors":"B. Bossoufi, Hala Alami Aroussi, M. E. Ghamrasni, Y. Ihedrane","doi":"10.1109/ECAI.2016.7861201","DOIUrl":null,"url":null,"abstract":"This paper presents a new contribution for the control technique of permanent magnets synchronous (PMSM) drive, this technique based on newly nonlinear Predictive Control. This control technique is based on the Taylor series expansion. The nonlinear predictive controller minimum variance (CPNLVM) has the objective of minimizing the error between the model output of the system and the output of the reference model. The operating principle of our approach is presented and analyzed at first, later the validation of our model is realized on Matlab & Simulink. The results obtained show the robustness and efficiency of this technique.","PeriodicalId":122809,"journal":{"name":"2016 8th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 8th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECAI.2016.7861201","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
This paper presents a new contribution for the control technique of permanent magnets synchronous (PMSM) drive, this technique based on newly nonlinear Predictive Control. This control technique is based on the Taylor series expansion. The nonlinear predictive controller minimum variance (CPNLVM) has the objective of minimizing the error between the model output of the system and the output of the reference model. The operating principle of our approach is presented and analyzed at first, later the validation of our model is realized on Matlab & Simulink. The results obtained show the robustness and efficiency of this technique.