Four-Channel Active Noise Control Modeling and Offline Simulation for Electric Bus Sound Quality Based on Two FxLMS Algorithms

Aiming at the consensus problem of slow convergence for the active noise control (ANC) model based on standard FxLMS algorithm that leads to performance degradation, this paper takes the error signal and its variation as the inputs of fuzzy logic control, and proposes an improved FxLMS algorithm by...

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Bibliographic Details
Published in:Acoustical physics 2024-02, Vol.70 (1), p.143-152
Main Authors: Zhang, E. L., Peng, Z. L., Li, Z. J., Lin, Y. B., Zhuo, J. M.
Format: Article
Language:English
Subjects:
Acoustic Ecology. Noises and Vibrations
Acoustics
Active noise control
Algorithms
Convergence
Error signals
Fuzzy control
Fuzzy logic
Loudness
Noise control
Noise measurement
Performance degradation
Physics
Physics and Astronomy
Sound pressure
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Summary:Aiming at the consensus problem of slow convergence for the active noise control (ANC) model based on standard FxLMS algorithm that leads to performance degradation, this paper takes the error signal and its variation as the inputs of fuzzy logic control, and proposes an improved FxLMS algorithm by fuzzy control mechanism with two-input-two-output TSK fuzzy rules (TSK-FxLMS); In addition, the four-channel ANC models based on standard FxLMS and TSK-FxLMS are constructed using the noise signals from four measuring points inside an electric bus under uniform and variable speed conditions, respectively. Ultimately, the offline simulation and acoustic parameter calculation results indicate that the A-weighted sound pressure level (ASPL) and loudness of the two FxLMS models within the low and middle frequencies are significantly reduced, whereas the TSK-FxLMS model has faster convergence rate, higher average reduction percentage of ASPL and loudness, which proves that the established four-channel TSK-FxLMS model has a better sound quality improvement effect than the standard FxLMS .
ISSN:1063-7710
1562-6865
DOI:10.1134/S1063771022600450