A self-tuning fuzzy filtered-U algorithm for the application of active noise cancellation

Cheng Yuan Chang; Kuo Kai Shyu

doi:10.1109/TCSI.2002.802350

A self-tuning fuzzy filtered-U algorithm for the application of active noise cancellation

Cheng Yuan Chang, Kuo Kai Shyu

Department of Electrical Engineering

Research output: Contribution to journal › Article › peer-review

17 Scopus citations

Abstract

This paper presents a fuzzy filtered-U algorithm for an active noise control (ANC) system. Instead of complex designing procedures, the proposed approach uses few mathematical transfer functions to design the ANC system. A fuzzy-based self-tuning algorithm is also provided in this paper to adjust the free parameters of the fuzzy filtered-U algorithm. In addition, the proposed method protects ANC systems against unstable poles such as occur in conventional filtered-U design. Finally, direct numerical simulations through the applications of duct noise demonstrate the effectiveness of the scheme.

Original language	English
Pages (from-to)	1325-1333
Number of pages	9
Journal	IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications
Volume	49
Issue number	9
DOIs	https://doi.org/10.1109/TCSI.2002.802350
State	Published - Sep 2002

Keywords

Active noise control
Filtered-U
Fuzzy
Self-tuning

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10.1109/TCSI.2002.802350

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abstract = "This paper presents a fuzzy filtered-U algorithm for an active noise control (ANC) system. Instead of complex designing procedures, the proposed approach uses few mathematical transfer functions to design the ANC system. A fuzzy-based self-tuning algorithm is also provided in this paper to adjust the free parameters of the fuzzy filtered-U algorithm. In addition, the proposed method protects ANC systems against unstable poles such as occur in conventional filtered-U design. Finally, direct numerical simulations through the applications of duct noise demonstrate the effectiveness of the scheme.",

keywords = "Active noise control, Filtered-U, Fuzzy, Self-tuning",

author = "Chang, {Cheng Yuan} and Shyu, {Kuo Kai}",

note = "Funding Information: Manuscript received January 17, 2001; revised June 7, 2002. This work was supported by the National Science Council, R. O. C., under Grant NSC-90-2213-E-231-001. This paper was recommended by Associate Editor W. B. Mikhael.",

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AU - Chang, Cheng Yuan

AU - Shyu, Kuo Kai

N1 - Funding Information: Manuscript received January 17, 2001; revised June 7, 2002. This work was supported by the National Science Council, R. O. C., under Grant NSC-90-2213-E-231-001. This paper was recommended by Associate Editor W. B. Mikhael.

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N2 - This paper presents a fuzzy filtered-U algorithm for an active noise control (ANC) system. Instead of complex designing procedures, the proposed approach uses few mathematical transfer functions to design the ANC system. A fuzzy-based self-tuning algorithm is also provided in this paper to adjust the free parameters of the fuzzy filtered-U algorithm. In addition, the proposed method protects ANC systems against unstable poles such as occur in conventional filtered-U design. Finally, direct numerical simulations through the applications of duct noise demonstrate the effectiveness of the scheme.

AB - This paper presents a fuzzy filtered-U algorithm for an active noise control (ANC) system. Instead of complex designing procedures, the proposed approach uses few mathematical transfer functions to design the ANC system. A fuzzy-based self-tuning algorithm is also provided in this paper to adjust the free parameters of the fuzzy filtered-U algorithm. In addition, the proposed method protects ANC systems against unstable poles such as occur in conventional filtered-U design. Finally, direct numerical simulations through the applications of duct noise demonstrate the effectiveness of the scheme.

KW - Active noise control

KW - Filtered-U

KW - Fuzzy

KW - Self-tuning

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JO - IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications

JF - IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications

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ER -

A self-tuning fuzzy filtered-U algorithm for the application of active noise cancellation

Abstract

Keywords

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