Active Noise Control System with Parallel On-Line Error Path Modeling Algorithm

1992 ◽  
Vol 39 (3) ◽  
pp. 119 ◽  
Author(s):  
Sen M. Kuo ◽  
Mingjie Wang ◽  
Ke Chen
Keyword(s):  
Control System ◽  
Noise Control ◽  
Active Noise Control ◽  
Path Modeling ◽  
Active Noise ◽  
On Line ◽  
Modeling Algorithm

scholarly journals A multi-tone active noise control system with a simplified local on-line secondary-path modeling

2018 ◽  
Vol 144 (6) ◽  
pp. EL515-EL521 ◽  
Author(s):  
Han Wang ◽  
Hongling Sun ◽  
Yunping Sun ◽  
Ming Wu ◽  
Jun Yang ◽  
...  
Keyword(s):  
Control System ◽  
Noise Control ◽  
Active Noise Control ◽  
Path Modeling ◽  
Active Noise ◽  
On Line ◽  
Secondary Path Modeling

scholarly journals Online secondary path modeling method with auxiliary noise power scheduling strategy for multi-channel adaptive active noise control system

2019 ◽  
Vol 38 (2) ◽  
pp. 740-752 ◽  
Author(s):  
Pu Yuxue ◽  
Shu Pengfei
Keyword(s):  
Control System ◽  
Noise Control ◽  
Active Noise Control ◽  
Variable Step Size ◽  
Noise Power ◽  
Path Modeling ◽  
Step Size ◽  
Scheduling Strategy ◽  
Active Noise ◽  
Secondary Path Modeling

Accurate model of secondary paths is very crucial for the multi-channel filtered-X least mean square algorithm applied in adaptive active noise control system. The auxiliary random noise technique is popular for online secondary path modeling during adaptive active noise control operation. This paper proposes a simplified variable step-size strategy and an effective auxiliary noise power scheduling strategy for the multi-channel filtered-X least mean square algorithm. Through a defined indirect error signal, the proposed method can guarantee every online secondary path modeling filter has its own exclusive variable step-size strategy to update their coefficients, and every injected noise has its own exclusive scheduling strategy considering all of the corresponding online secondary path modeling filters. The proposed method can improve the adaptive performance and simplifies the complexity of multi-channel adaptive active noise control system. Computer simulations show that the proposed method gives much better noise reduction and secondary path modeling accuracy at a somewhat faster convergence rate comparing with the competing methods.

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