Active noise control with online feedback-path modeling using adaptive notch filter

Author(s):  
Tao Bai ◽  
Yegui Xiao ◽  
Yaping Ma ◽  
Jianming Ding ◽  
Jianhui Lin
2019 ◽  
Vol 19 (01) ◽  
pp. 2050008
Author(s):  
Abdul Haseeb ◽  
Muhammad Tufail ◽  
Shakeel Ahmed ◽  
Muhammad Rehan ◽  
Amna Majid ◽  
...  

Acoustic feedback is the main problem associated with (broadband) active noise control (ANC) in feed-forward configuration. To solve this problem, auxiliary noise is injected into the ANC system to have accurate model of the feedback path. The conventional approaches substantially model the feedback path at the cost of degradation in the noise reduction performance (NRP) and vice versa. Here, we propose a fuzzy logic-based gain scheduling (of auxiliary noise) for online feedback path modeling and neutralization (FBPMN). The fuzzy controller computes the instantaneous gain for auxiliary noise based on two inputs, the first input gives information about modeling status of FBPMN filter while the second input gives information regarding variance of the disturbance signal for the adaptive FBPMN filter. Furthermore, variable step-size (VSS) is used for the adaptation of FBPMN filter that uses a larger value of step-size during modeling (phase) of FBPMN filter for fast adaptation and a smaller value when the feedback path has been (adequately) modeled. Fuzzy gain scheduler together with VSS in FBPMN filter improves both the NRP and feedback path modeling characteristics. Moreover, the proposed method does not require initial offline modeling of the feedback path thereby demonstrating complete online operation. To make the system computationally efficient, a look-up table-based approach is also proposed in this paper. Simulations results are presented to demonstrate the effectiveness of the proposed method.


2021 ◽  
Vol 69 (2) ◽  
pp. 136-145
Author(s):  
S. Roopa ◽  
S.V. Narasimhan

A stable feedback active noise control (FBANC) system with an improved performance in a broadband disturbance environment is proposed in this article. This is achieved by using a Steiglitz-McBride adaptive notch filter (SM-ANF) and robust secondary path identification (SPI) both based on variable step size Griffiths least mean square (LMS) algorithm. The broadband disturbance severely affects not only FBANC input synthesized but also the SPI.TheSM-ANFestimated signal has narrowband component that is utilized for the FBANC input synthesis. Further, the SM-ANF error has broadband component utilized to get the desired signal for SPI. The use of variable step size Griffiths gradient LMS algorithm for SPI enables the removal of broadband disturbance and non-stationary disturbance from the available desired signal for better SPI. For a narrowband noise field, the proposed FBANC improves the convergence rate significantly (20 times) and the noise reduction from 10 dB to 15 dB (50%improvement) over the conventional FBANC (without SM-ANF and variable step size Griffiths LMS adaptation for SPI).


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