{"title":"驱动系统的神经模糊鲁棒控制器","authors":"Y. Dote, M. Strefezza, A. Suyitno","doi":"10.1109/ISIE.1993.268801","DOIUrl":null,"url":null,"abstract":"The authors describe and approximate zeroing with an equivalent disturbance observer and predictive controller for drive systems. Then this linear controller structure is changed by fuzzy logic such that the controller makes the system respond quickly if the error is large and vice versa in order to obtain a robust controller which is insensitive to both the plant noise and the observation noise. Next, a variable structure PI controller by fuzzy logic for the drive systems is introduced. Then, this control scheme is implemented with neural networks. These controllers are realized with digital signal processors. The experimental results are given. Lastly, the applications of neuro fuzzy methods to inverters, converters, motion controls and sensors are explained.<<ETX>>","PeriodicalId":267349,"journal":{"name":"ISIE '93 - Budapest: IEEE International Symposium on Industrial Electronics Conference Proceedings","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Neuro fuzzy robust controllers for drive systems\",\"authors\":\"Y. Dote, M. Strefezza, A. Suyitno\",\"doi\":\"10.1109/ISIE.1993.268801\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The authors describe and approximate zeroing with an equivalent disturbance observer and predictive controller for drive systems. Then this linear controller structure is changed by fuzzy logic such that the controller makes the system respond quickly if the error is large and vice versa in order to obtain a robust controller which is insensitive to both the plant noise and the observation noise. Next, a variable structure PI controller by fuzzy logic for the drive systems is introduced. Then, this control scheme is implemented with neural networks. These controllers are realized with digital signal processors. The experimental results are given. Lastly, the applications of neuro fuzzy methods to inverters, converters, motion controls and sensors are explained.<<ETX>>\",\"PeriodicalId\":267349,\"journal\":{\"name\":\"ISIE '93 - Budapest: IEEE International Symposium on Industrial Electronics Conference Proceedings\",\"volume\":\"65 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1993-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ISIE '93 - Budapest: IEEE International Symposium on Industrial Electronics Conference Proceedings\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISIE.1993.268801\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISIE '93 - Budapest: IEEE International Symposium on Industrial Electronics Conference Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIE.1993.268801","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The authors describe and approximate zeroing with an equivalent disturbance observer and predictive controller for drive systems. Then this linear controller structure is changed by fuzzy logic such that the controller makes the system respond quickly if the error is large and vice versa in order to obtain a robust controller which is insensitive to both the plant noise and the observation noise. Next, a variable structure PI controller by fuzzy logic for the drive systems is introduced. Then, this control scheme is implemented with neural networks. These controllers are realized with digital signal processors. The experimental results are given. Lastly, the applications of neuro fuzzy methods to inverters, converters, motion controls and sensors are explained.<>