{"title":"基于预测误差法和培养粒子群算法的电机作动器模型辨识","authors":"S. Kiviluoto, Ying Wu, K. Zenger, X. Gao","doi":"10.1109/ICSENGT.2011.5993424","DOIUrl":null,"url":null,"abstract":"This paper discusses identification of an actuator model, which has been built inside a two-pole induction motor in order to control rotor vibrations. The methods used for identification are prediction error method and cultural particle swarm optimization with mutation. The first-mentioned method produces a black box model with correspondence to input-output measurements. The second method is used to identify parameters of a linear time-invariant state-space model, which is based on electromechanical equations. The results are compared in time domain and in frequency domain.","PeriodicalId":346890,"journal":{"name":"2011 IEEE International Conference on System Engineering and Technology","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Identification of actuator model in an electrical machine by prediction error method and cultural particle swarm optimization\",\"authors\":\"S. Kiviluoto, Ying Wu, K. Zenger, X. Gao\",\"doi\":\"10.1109/ICSENGT.2011.5993424\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper discusses identification of an actuator model, which has been built inside a two-pole induction motor in order to control rotor vibrations. The methods used for identification are prediction error method and cultural particle swarm optimization with mutation. The first-mentioned method produces a black box model with correspondence to input-output measurements. The second method is used to identify parameters of a linear time-invariant state-space model, which is based on electromechanical equations. The results are compared in time domain and in frequency domain.\",\"PeriodicalId\":346890,\"journal\":{\"name\":\"2011 IEEE International Conference on System Engineering and Technology\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE International Conference on System Engineering and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSENGT.2011.5993424\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE International Conference on System Engineering and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSENGT.2011.5993424","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Identification of actuator model in an electrical machine by prediction error method and cultural particle swarm optimization
This paper discusses identification of an actuator model, which has been built inside a two-pole induction motor in order to control rotor vibrations. The methods used for identification are prediction error method and cultural particle swarm optimization with mutation. The first-mentioned method produces a black box model with correspondence to input-output measurements. The second method is used to identify parameters of a linear time-invariant state-space model, which is based on electromechanical equations. The results are compared in time domain and in frequency domain.