A novel adaptive step-size hybrid active noise control system

2021 ◽  
Vol 182 ◽  
pp. 108285
Author(s):  
Yao Jiang ◽  
Shuming Chen ◽  
Hao Meng ◽  
Zhengdao Zhou ◽  
Wei Lv
Keyword(s):  
Control System ◽  
Noise Control ◽  
Active Noise Control ◽  
Step Size ◽  
Adaptive Step Size ◽  
Active Noise ◽  
Adaptive Step

Implementation of Single and Multiple Adaptive Step Size Algorithm to ANC

2004 ◽  
Author(s):  
Yesim Sabah ◽  
Masaaki Okuma ◽  
Minoru Okubo
Keyword(s):  
Steady State ◽  
Noise Control ◽  
Active Noise Control ◽  
Lms Algorithm ◽  
Step Size ◽  
Adaptive Step Size ◽  
Active Noise ◽  
Control Application ◽  
Adaptive Step ◽  
State Error

The purpose of this paper is to investigate a modified adaptive step size algorithm and implement to active noise control (ANC) system. It is well-known that there is a trade-off between steady state error and convergence rate depending on the step size. This study shows that the new algorithm can track changes in dynamic characteristics of ANC system as well as produce a low steady state error. Simulation results are presented to compare the performance of the new algorithm to basic LMS algorithm. Although there have been several studies for adaptive step size algorithm, no quantitative analysis has yet been reported for real time active noise control application as far as the authors know. Experimental results are presented for a duct system. The results indicate that the new algorithm provides better performance than the fixed step size FXLMS algorithm.

Implementation of Single and Multiple Adaptive Step-Size Algorithm to ANC

2007 ◽  
Vol 130 (1) ◽  
Author(s):  
Yesim Sabah ◽  
Masaaki Okuma ◽  
Minoru Okubo
Keyword(s):  
Steady State ◽  
Noise Control ◽  
Active Noise Control ◽  
Mean Square ◽  
Least Mean Square ◽  
Step Size ◽  
Adaptive Step Size ◽  
Active Noise ◽  
Adaptive Step ◽  
State Error

The purpose of this paper is to investigate a modified adaptive step-size algorithm and implement an active noise control (ANC) system. It is well known that there is a tradeoff between steady state error and convergence rate depending on the step size. This study shows that the new algorithm can track changes in the dynamic characteristics of the ANC system as well as produce a low steady state error. Simulation results are presented to compare the performance of the new algorithm to the basic least mean square (LMS) algorithm. Although there have been several studies of adaptive step-size algorithms, no quantitative analysis has yet been reported for real time active noise control application as far as the authors know. Experimental results are presented for a duct system. The results indicate that the new algorithm provides better performance than the fixed step-size filtered-X least mean square (FXLMS) algorithm.

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 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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