{"title":"一种应用于主动噪声控制的自整定模糊滤波u算法","authors":"Cheng-Yuan Chang, K. Shyu","doi":"10.1109/IECON.2001.976528","DOIUrl":null,"url":null,"abstract":"The proposed fuzzy method guarantees an active noise control (ANC) system against unstable poles as in the conventional filtered-U design; the performance is hence improved. Besides, the fuzzy algorithm uses the input-output data relationships of the ANC system instead to construct the control rules. The design complexity is consequently reduced.","PeriodicalId":345608,"journal":{"name":"IECON'01. 27th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.37243)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A self-tuning fuzzy filtered-U algorithm with the application of active noise control\",\"authors\":\"Cheng-Yuan Chang, K. Shyu\",\"doi\":\"10.1109/IECON.2001.976528\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The proposed fuzzy method guarantees an active noise control (ANC) system against unstable poles as in the conventional filtered-U design; the performance is hence improved. Besides, the fuzzy algorithm uses the input-output data relationships of the ANC system instead to construct the control rules. The design complexity is consequently reduced.\",\"PeriodicalId\":345608,\"journal\":{\"name\":\"IECON'01. 27th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.37243)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IECON'01. 27th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.37243)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IECON.2001.976528\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IECON'01. 27th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.37243)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IECON.2001.976528","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A self-tuning fuzzy filtered-U algorithm with the application of active noise control
The proposed fuzzy method guarantees an active noise control (ANC) system against unstable poles as in the conventional filtered-U design; the performance is hence improved. Besides, the fuzzy algorithm uses the input-output data relationships of the ANC system instead to construct the control rules. The design complexity is consequently reduced.