{"title":"Fuzzy PID control of the planar switched reluctance motor for precision positioning","authors":"X. Fu, G. Cao, S. Huang, C. Wu","doi":"10.1109/PESA.2017.8277765","DOIUrl":null,"url":null,"abstract":"This paper proposes a fuzzy proportional-integral-derivative (PID) control for the planar switched reluctance motor (PSRM) to realize precision positioning. The mathematical model of the PSRM is first given. Then a fuzzy proportional-derivative (PD) controller is designed for the PSRM, which features strong robustness to parametric variation, uncertainty, and interference. The fuzzy PD control of the PSRM is carried out via simulation based on MATLAB. Compared with the PD controller, the control performance of the PSRM with the fuzzy PD controller is superior. The effectiveness of the proposed control is verified through the simulation results.","PeriodicalId":223569,"journal":{"name":"2017 7th International Conference on Power Electronics Systems and Applications - Smart Mobility, Power Transfer & Security (PESA)","volume":"145 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 7th International Conference on Power Electronics Systems and Applications - Smart Mobility, Power Transfer & Security (PESA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PESA.2017.8277765","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This paper proposes a fuzzy proportional-integral-derivative (PID) control for the planar switched reluctance motor (PSRM) to realize precision positioning. The mathematical model of the PSRM is first given. Then a fuzzy proportional-derivative (PD) controller is designed for the PSRM, which features strong robustness to parametric variation, uncertainty, and interference. The fuzzy PD control of the PSRM is carried out via simulation based on MATLAB. Compared with the PD controller, the control performance of the PSRM with the fuzzy PD controller is superior. The effectiveness of the proposed control is verified through the simulation results.