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http://dx.doi.org/10.5762/KAIS.2019.20.3.570

Design of IIR Structure Active Mufflers using Stabilized Filter Algorithms  

Ahn, Dong-Jun (Department of Automotive Engineering, Ajou Motor College)
Nam, Hyun-Do (Department of Electronics & Electrical Engineering, Dankook University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.20, no.3, 2019 , pp. 570-575 More about this Journal
Abstract
Active muffler is implemented by applying active noise control technique to reduce exhaust noise of automobile muffler. Conventional Filtered_x LMS algorithm has a problem that the degree of control filter becomes very large and convergence deteriorates when acoustic feedback is present. The recursive LMS algorithm can compensate for this problem because it can be easily diverted in the adaptive filter adaptation process. In this paper, the structure of the primary path and the secondary path transfer function is designed as the IIR filter to improve the convergence performance and the computational burden, and the stabilization filter algorithm is applied to secure stability which is a disadvantage of the IIR filter structure. The stabilization filter algorithm plays a role of pulling the pole into the unit circle to prevent the pole of the transfer function corresponding to the acoustic feedback from diverging during the adaptation process. In this way, the computational burden of the active muffler system and the convergence performance can be improved. In order to show the usefulness of the proposed system, we compared the performance of the proposed Filtered_x LMS algorithm with the performance of the proposed system for the exhaust sound of a diesel engine, which is a variable environment. Compared to conventional algorithm, proposed algorithm's computational burden is less than half, and convergence performances are more than 4 times.
Keywords
Adaptive Filter; Active Mufflers; Active Noise Control; Filtered_U LMS Algorithm; Stabilized Filter;
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Times Cited By KSCI : 1  (Citation Analysis)
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1 D. J. Ahn, "Multi-channel Active control system designs using fuzzy logic stabilized algorithms," Journal of Korea Academia-Industrial cooperation Society, Vol. 13, N0. 8, pp. 3647-3653. DOI: https://doi.org/10.5762/KAIS.2012.13.8.3647   DOI
2 Widrow B. and Stearns S.D., Adaptive Signal Processing, Eglewood Cliffs, NJ: Prentice-Hall, 1985.
3 Nam H. D. and Seo S. D., Yoon K. J., Ahn D. J., "Stabilized multi-channel IIR filters for active control of noise in a duct," ICSV13-Vienna, 2006.
4 D.J. Ahn, K.H. Park, S.H. Kim, H.D. Nam, "Design of Fuzzy Logic Adaptive Filters for Active Mufflers," Trans. of KASE, Vol. 19, No. 4, pp. 84-90, 2011.
5 Elliott S.J. and Nelson P.A., "Models for describing active noise control in ducts," ISVR Techincal Report No.127, University of Southampton, U.K., 1984.
6 Lueq P., "Process of silencing sound oscillations," US Patent 2043 416 1934.
7 D. J. Ahn, "Design of adaptive filters for active noise control," Ph. D. theses, Dankook Univ. Dept. of Elec., 1995.
8 Elliott S.J. and Nelson P.A., "The active control of sound," Electronics and Communication Eng. Jour., pp.127-136, 1990. DOI: http:/dx.doi.org/10.1049/ecej:19900032   DOI
9 Kuo S.M and Morgan D.R, Active Noise Control Systems, John Wiley, 1995.