{"title":"基于结构约束LQR LMI准则的PMSM PI电流控制器整定","authors":"L. Pohl, Ondrej Bartik","doi":"10.1109/SPEC.2018.8635836","DOIUrl":null,"url":null,"abstract":"In this paper the convex optimization technique is proposed for parameter tuning of a PI controller. Presented non-iterative two step procedure is able to optimize the coefficients of a structured output feedback matrix using the LQR cost function. It is also shown that the matrix coefficients can be linked to PI controller parameters simply by extending the state space model of the plant. The capability of this method to optimize controllers for MIMO plants is demonstrated on current control of the real PMSM.","PeriodicalId":335893,"journal":{"name":"2018 IEEE 4th Southern Power Electronics Conference (SPEC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"PMSM PI Current Controller Tuning Using Structurally Constrain LQR LMI Criteria for MIMO Plants\",\"authors\":\"L. Pohl, Ondrej Bartik\",\"doi\":\"10.1109/SPEC.2018.8635836\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper the convex optimization technique is proposed for parameter tuning of a PI controller. Presented non-iterative two step procedure is able to optimize the coefficients of a structured output feedback matrix using the LQR cost function. It is also shown that the matrix coefficients can be linked to PI controller parameters simply by extending the state space model of the plant. The capability of this method to optimize controllers for MIMO plants is demonstrated on current control of the real PMSM.\",\"PeriodicalId\":335893,\"journal\":{\"name\":\"2018 IEEE 4th Southern Power Electronics Conference (SPEC)\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 4th Southern Power Electronics Conference (SPEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPEC.2018.8635836\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 4th Southern Power Electronics Conference (SPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPEC.2018.8635836","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
PMSM PI Current Controller Tuning Using Structurally Constrain LQR LMI Criteria for MIMO Plants
In this paper the convex optimization technique is proposed for parameter tuning of a PI controller. Presented non-iterative two step procedure is able to optimize the coefficients of a structured output feedback matrix using the LQR cost function. It is also shown that the matrix coefficients can be linked to PI controller parameters simply by extending the state space model of the plant. The capability of this method to optimize controllers for MIMO plants is demonstrated on current control of the real PMSM.