{"title":"Sensorless vector control of asynchronous machine based on reduced order Kalman filter","authors":"E. Solodkiy, D. Dadenkov, A. M. Kostygov","doi":"10.1109/ACED.2018.8341710","DOIUrl":null,"url":null,"abstract":"The article describes sensorless vector control of the asynchronous machine based on Kalman filter. A control system block diagram is presented along with a functional scheme of the original speed observer using dynamic system state vector filter estimator. The synthesis of current regulator using machine parameters determined by inverse r model is shown. The method of a control matrix dimension reduction is proposed by removal the flux linkage calculations out of Kalman filter algorithms. Current and speed regulators, as well as a flux estimator, were implemented in the Mexbios Development Studio simulation environment. The robustness of a speed observer and the efficiency of the asynchronous machine sensorless control system were confirmed by the simulation results.","PeriodicalId":199924,"journal":{"name":"2018 17th International Ural Conference on AC Electric Drives (ACED)","volume":"7 18","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 17th International Ural Conference on AC Electric Drives (ACED)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACED.2018.8341710","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
The article describes sensorless vector control of the asynchronous machine based on Kalman filter. A control system block diagram is presented along with a functional scheme of the original speed observer using dynamic system state vector filter estimator. The synthesis of current regulator using machine parameters determined by inverse r model is shown. The method of a control matrix dimension reduction is proposed by removal the flux linkage calculations out of Kalman filter algorithms. Current and speed regulators, as well as a flux estimator, were implemented in the Mexbios Development Studio simulation environment. The robustness of a speed observer and the efficiency of the asynchronous machine sensorless control system were confirmed by the simulation results.
本文介绍了基于卡尔曼滤波的异步电机无传感器矢量控制。给出了控制系统框图,并给出了采用动态系统状态向量滤波估计器的原速度观测器的功能方案。给出了利用逆r模型确定的电机参数综合电流调节器的方法。提出了一种控制矩阵降维的方法,去掉卡尔曼滤波算法中的磁链计算。电流和速度调节器以及通量估计器在Mexbios Development Studio模拟环境中实现。仿真结果验证了速度观测器的鲁棒性和异步电机无传感器控制系统的有效性。