A New Variable Step Size Algorithm Based Hybrid Active Noise Control System for Gaussian Noise with Impulsive Interference

2020 ◽  
Author(s):  
Wenzhao Zhu ◽  
Lei Luo ◽  
Jinwei Sun ◽  
Mads Graesboll Christensen
Keyword(s):  
Control System ◽  
Gaussian Noise ◽  
Noise Control ◽  
Active Noise Control ◽  
Variable Step Size ◽  
Step Size ◽  
Impulsive Interference ◽  
Active Noise ◽  
Variable Step

Adaptive IIR Filter Using Variable Step Size for Active Noise Control Inside a Short Duct

2008 ◽  
Author(s):  
Ho-Wuk Kim ◽  
Sang-Kwon Lee
Keyword(s):  
Control System ◽  
Noise Control ◽  
Active Noise Control ◽  
Fir Filter ◽  
Variable Step Size ◽  
Step Size ◽  
Iir Filter ◽  
Active Noise ◽  
Lms Filter ◽  
Variable Step

FIR filter for a adaptive filter algorithm, is mostly used for an active noise control system. However, FIR filter needs to have more large size of the filter length than it of IIR filter. Therefore, the control system using FIR adaptive filter has slow calculation time. In the active noise control system of the short duct, the reference signal can be affected by the output signal, so IIR filter for ARMA system can be more suitable for the active noise control of the short duct than FIR filter for MA system. In this paper, the recursive LMS filter, which is adaptive IIR filter, is applicated for the active noise control inside the short duct. For faster convergence and more accurate control, a variable step size algorithm is introduced for this recursive LMS filter (R-VSSLMS filter). Using this algorithm and considering the secondary path, the filtered-u R-VSSLMS is conducted successfully on the real experiment in the short duct. The performance of the active control using the filtered-u R-VSSLMS filter, is compared with the performance of the active control using a filtered-x LMS filter.

scholarly journals Multichannel active noise control system using variable step size algorithms

2015 ◽  
Vol 18 (3) ◽  
pp. 61-71
Author(s):  
Ngan Vuong Thuy Nguyen ◽  
Long Duc Tran ◽  
Tho Thi Minh Tran ◽  
Tuan Van Huynh
Keyword(s):  
Control System ◽  
Real Time ◽  
Noise Control ◽  
Active Noise Control ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Step Size ◽  
Feed Forward ◽  
Active Noise ◽  
Variable Step

This paper presents the feed-forward multichannel active noise control which was simulated on LabVIEW and experimented on two channel feed-forward active noise control in real-time. The simulation of feed-forward multichannel active noise control system was built on LabVIEW by using FxLMS algorithm and other algorithms such as Variable Step-size (VSS) and saturation compensation. Moreover, LMS and VSS LMS algorithm were used to train the secondary path in order to improve the convergence speed and stabilization of ANC system in the real-time. The experimental results show that the ANC system in real-time using variable step-size and without using variable step-size algorithm work effectively with noise sources which were synthesized from one to three frequencies. The noise level in these cases decreased around 12 dB - 35 dB and the noise reduction radius measured is about 3 cm around the microphone.

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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