{"title":"基于ANFIS的AZSPWM方法降低异步电机驱动共模电压","authors":"R. Lingangouda, Pradeep B. Jyoti","doi":"10.11591/ijape.v11.i4.pp319-324","DOIUrl":null,"url":null,"abstract":"Space vector pulse width modulation (SVPWM) is a popular technique in the field of variable frequency induction motor drives. It gives better working and good direct current bus utilization in comparison to the sinusoidal PWM (SPWM) method. However, it decreases harmonic fluctuations and generates high common mode voltage (CMV) fluctuations, which results in common mode currents inside the motor. Hence, the performance of the motor may be deteriorated. To reduce the CMV, this paper presents a family of active zero state PWM (AZSPWM) methods using an adaptive neuro-fuzzy interference system (ANFIS). The proposed approach uses a five-layer hybrid learning algorithm for training the network. The training data is obtained from the classical SVPWM method. To analyze the proposed PWM methods, simulation is carried out using MATLAB and evaluated.","PeriodicalId":340072,"journal":{"name":"International Journal of Applied Power Engineering (IJAPE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"ANFIS based AZSPWM methods for reduction common mode voltage in asynchronous motor drive\",\"authors\":\"R. Lingangouda, Pradeep B. Jyoti\",\"doi\":\"10.11591/ijape.v11.i4.pp319-324\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Space vector pulse width modulation (SVPWM) is a popular technique in the field of variable frequency induction motor drives. It gives better working and good direct current bus utilization in comparison to the sinusoidal PWM (SPWM) method. However, it decreases harmonic fluctuations and generates high common mode voltage (CMV) fluctuations, which results in common mode currents inside the motor. Hence, the performance of the motor may be deteriorated. To reduce the CMV, this paper presents a family of active zero state PWM (AZSPWM) methods using an adaptive neuro-fuzzy interference system (ANFIS). The proposed approach uses a five-layer hybrid learning algorithm for training the network. The training data is obtained from the classical SVPWM method. To analyze the proposed PWM methods, simulation is carried out using MATLAB and evaluated.\",\"PeriodicalId\":340072,\"journal\":{\"name\":\"International Journal of Applied Power Engineering (IJAPE)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Applied Power Engineering (IJAPE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.11591/ijape.v11.i4.pp319-324\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Applied Power Engineering (IJAPE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11591/ijape.v11.i4.pp319-324","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
ANFIS based AZSPWM methods for reduction common mode voltage in asynchronous motor drive
Space vector pulse width modulation (SVPWM) is a popular technique in the field of variable frequency induction motor drives. It gives better working and good direct current bus utilization in comparison to the sinusoidal PWM (SPWM) method. However, it decreases harmonic fluctuations and generates high common mode voltage (CMV) fluctuations, which results in common mode currents inside the motor. Hence, the performance of the motor may be deteriorated. To reduce the CMV, this paper presents a family of active zero state PWM (AZSPWM) methods using an adaptive neuro-fuzzy interference system (ANFIS). The proposed approach uses a five-layer hybrid learning algorithm for training the network. The training data is obtained from the classical SVPWM method. To analyze the proposed PWM methods, simulation is carried out using MATLAB and evaluated.