Particle swarm optimization based novel adaptive step-size FxLMS algorithm with reference signal smoothing processor for feedforward active noise control systems

2021 ◽  
Vol 174 ◽  
pp. 107796
Author(s):  
Hao Meng ◽  
Shuming Chen
Keyword(s):  
Particle Swarm Optimization ◽  
Control Systems ◽  
Reference Signal ◽  
Active Noise Control ◽  
Step Size ◽  
Swarm Optimization ◽  
Adaptive Step Size ◽  
Active Noise ◽  
Fxlms Algorithm ◽  
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.

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

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.

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