A new variable step size LMS algorithm-based method for improved online secondary path modeling in active noise control systems

2006 ◽  
Vol 14 (2) ◽  
pp. 720-726 ◽  
Author(s):  
M.T. Akhtar ◽  
M. Abe ◽  
M. Kawamata
Keyword(s):  
Control Systems ◽  
Noise Control ◽  
Active Noise Control ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Path Modeling ◽  
Step Size ◽  
Active Noise ◽  
Variable Step ◽  
Secondary Path Modeling

Online secondary path modeling in multichannel active noise control systems using variable step size

2008 ◽  
Vol 88 (8) ◽  
pp. 2019-2029 ◽  
Author(s):  
Muhammad Tahir Akhtar ◽  
Masahide Abe ◽  
Masayuki Kawamata ◽  
Akinori Nishihara
Keyword(s):  
Control Systems ◽  
Noise Control ◽  
Active Noise Control ◽  
Variable Step Size ◽  
Path Modeling ◽  
Step Size ◽  
Active Noise ◽  
Variable Step ◽  
Secondary Path Modeling

Improved stability performance of a feedback active noise control using a Steiglitz-McBride adaptive notch filter and robust secondary path identification based on variable step size Griffiths LMS algorithm

2021 ◽  
Vol 69 (2) ◽  
pp. 136-145
Author(s):  
S. Roopa ◽  
S.V. Narasimhan
Keyword(s):  
Noise Control ◽  
Active Noise Control ◽  
Notch Filter ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Step Size ◽  
Adaptive Notch Filter ◽  
Active Noise ◽  
Variable Step ◽  
Feedback Active Noise Control

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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