{"title":"模糊逻辑在主动噪声控制中的应用","authors":"O. Kipersztok, Ron Hammond","doi":"10.1109/ISUMA.1995.527759","DOIUrl":null,"url":null,"abstract":"The paper describes the use of fuzzy logic for the active control of a distributed source of broadband noise modelled by multiple compact sources with low correlation between them. The early signals are collected from microphones placed near the sources. Control is provided by a cancelling noise source, in the form of a loudspeaker, between the early microphones and a control microphone placed at a location where noise reduction is desired. The fuzzy controller uses the cross correlation between early and control microphones and the signal to noise ratio of the cross correlation estimate to adjust the coefficients of a filter driving the loudspeaker. The fuzzy controller showed considerably higher noise attenuation levels when compared to the performance of an optimal linear filter controller. In addition to its ease of implementation and to making explicit the heuristic control rules, the fuzzy system localizes the control for each early microphone loudspeaker pair. The use of several, independent control units offers improved computational efficiency, which is critical for situations when the source is nonstationary, and offers the potential for parallelization.","PeriodicalId":298915,"journal":{"name":"Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"The use of fuzzy logic in active noise control\",\"authors\":\"O. Kipersztok, Ron Hammond\",\"doi\":\"10.1109/ISUMA.1995.527759\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper describes the use of fuzzy logic for the active control of a distributed source of broadband noise modelled by multiple compact sources with low correlation between them. The early signals are collected from microphones placed near the sources. Control is provided by a cancelling noise source, in the form of a loudspeaker, between the early microphones and a control microphone placed at a location where noise reduction is desired. The fuzzy controller uses the cross correlation between early and control microphones and the signal to noise ratio of the cross correlation estimate to adjust the coefficients of a filter driving the loudspeaker. The fuzzy controller showed considerably higher noise attenuation levels when compared to the performance of an optimal linear filter controller. In addition to its ease of implementation and to making explicit the heuristic control rules, the fuzzy system localizes the control for each early microphone loudspeaker pair. The use of several, independent control units offers improved computational efficiency, which is critical for situations when the source is nonstationary, and offers the potential for parallelization.\",\"PeriodicalId\":298915,\"journal\":{\"name\":\"Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-03-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISUMA.1995.527759\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISUMA.1995.527759","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The paper describes the use of fuzzy logic for the active control of a distributed source of broadband noise modelled by multiple compact sources with low correlation between them. The early signals are collected from microphones placed near the sources. Control is provided by a cancelling noise source, in the form of a loudspeaker, between the early microphones and a control microphone placed at a location where noise reduction is desired. The fuzzy controller uses the cross correlation between early and control microphones and the signal to noise ratio of the cross correlation estimate to adjust the coefficients of a filter driving the loudspeaker. The fuzzy controller showed considerably higher noise attenuation levels when compared to the performance of an optimal linear filter controller. In addition to its ease of implementation and to making explicit the heuristic control rules, the fuzzy system localizes the control for each early microphone loudspeaker pair. The use of several, independent control units offers improved computational efficiency, which is critical for situations when the source is nonstationary, and offers the potential for parallelization.