Pub Date : 2022-05-26DOI: 10.1109/ICSSE55923.2022.9948228
Hung-Yuan Chung, Yao-Liang Chung, Yi-Hao Jhu
The purpose of this research is to overcome the disadvantages of the classic direct torque control (Classic-DTC) in the switching table scheme. The approach is based on torque angle control, which is based on the relationship between the stator flux and rotor flux space vectors of the intuitive control system. DTC can achieve rapid torque response, which can cause high torque ripple and noise. In order to reduce stator flux ripple and torque ripple, the space-vector pulse width modulation (SVPWM) generates different switching states for each sampling time, and adapts to overcome the aforementioned problems, especially flux ripple and torque ripple. The reference flux is kept constant in this paper, and a fuzzy controller is used to compensate the reference flux in order to lessen the errors of the transient state response. In order to demonstrate this method, it was installed on a permanent magnet synchronous motor (PMSM) controller. Finally, the control system is implemented by digital signal processor TMS320F28335 to achieve high speed and accurate control of the system.
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Pub Date : 2022-05-26DOI: 10.1109/ICSSE55923.2022.9948239
Presents the copyright information for the conference. May include reprint permission information.
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{"title":"IEEE Copyright and Consent Form","authors":"","doi":"10.1109/ICSSE55923.2022.9948239","DOIUrl":"https://doi.org/10.1109/ICSSE55923.2022.9948239","url":null,"abstract":"Presents the copyright information for the conference. May include reprint permission information.","PeriodicalId":220599,"journal":{"name":"2022 International Conference on System Science and Engineering (ICSSE)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116800644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-26DOI: 10.1109/ICSSE55923.2022.9947359
Wei-Ting Yen, Yun Jie Zhang, Kuo-Hsuan Chung, L. Lin, Yue-Shan Chang
The assessment of mental status is an important task in psychiatry. But the impact of the COVID-19 epidemic has reduced the number of face-to-face assessments with physicians, and thus making it difficult. In recent years, some studies have used EEG (electroencephalogram) to help assess depression or mental state. Users can thus further assess mental state through simple EEG measurement. Since the EEG measurement will obtain multiple frequency bands related to mental or emotion state, if only one frequency band is used to evaluate a specific emotion or mental state, it may be insufficient. Some studies have proposed an ensemble method of multiple frequency bands for emotion recognition. In this study, we will use ensemble multi-bands EEG frequency to do and assist mental state or depression assessment. Through the method of ensemble learning, we integrate the frequency bands which is mainly related to mental state to assist the evaluation of mental state. From the experimental results, we can find that this method has a good effect.
{"title":"Ensembling EEG bands for Mental State Assessment","authors":"Wei-Ting Yen, Yun Jie Zhang, Kuo-Hsuan Chung, L. Lin, Yue-Shan Chang","doi":"10.1109/ICSSE55923.2022.9947359","DOIUrl":"https://doi.org/10.1109/ICSSE55923.2022.9947359","url":null,"abstract":"The assessment of mental status is an important task in psychiatry. But the impact of the COVID-19 epidemic has reduced the number of face-to-face assessments with physicians, and thus making it difficult. In recent years, some studies have used EEG (electroencephalogram) to help assess depression or mental state. Users can thus further assess mental state through simple EEG measurement. Since the EEG measurement will obtain multiple frequency bands related to mental or emotion state, if only one frequency band is used to evaluate a specific emotion or mental state, it may be insufficient. Some studies have proposed an ensemble method of multiple frequency bands for emotion recognition. In this study, we will use ensemble multi-bands EEG frequency to do and assist mental state or depression assessment. Through the method of ensemble learning, we integrate the frequency bands which is mainly related to mental state to assist the evaluation of mental state. From the experimental results, we can find that this method has a good effect.","PeriodicalId":220599,"journal":{"name":"2022 International Conference on System Science and Engineering (ICSSE)","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133199872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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