Novel active noise control based on a robust filtered-x normalized least mean square sign algorithm against large measurement and impulsive noises

Author(s):  
Dong Woo Kim ◽  
JunHui Lee ◽  
Hyeon-Woo Na ◽  
Chan Park ◽  
PooGyeon Park
2009 ◽  
Vol 16 (3) ◽  
pp. 325-334 ◽  
Author(s):  
Ya-li Zhou ◽  
Qi-zhi Zhang ◽  
Tao Zhang ◽  
Xiao-dong Li ◽  
Woon-seng Gan

In practical active noise control (ANC) systems, the primary path and the secondary path may be nonlinear and time-varying. It has been reported that the linear techniques used to control such ANC systems exhibit degradation in performance. In addition, the actuators of an ANC system very often have nonminimum-phase response. A linear controller under such situations yields poor performance. A novel functional link artificial neural network (FLANN)-based simultaneous perturbation stochastic approximation (SPSA) algorithm, which functions as a nonlinear mode-free (MF) controller, is proposed in this paper. Computer simulations have been carried out to demonstrate that the proposed algorithm outperforms the standard filtered-x least mean square (FXLMS) algorithm, and performs better than the recently proposed filtered-s least mean square (FSLMS) algorithm when the secondary path is time-varying. This observation implies that the SPSA-based MF controller can eliminate the need of the modeling of the secondary path for the ANC system.


2017 ◽  
Vol 95 ◽  
pp. 14006
Author(s):  
Rahimie Mustafa ◽  
Anuar Mikdad Muad ◽  
Shahrizal Jelani ◽  
Ahmad Nur Alifa Abdul Razap

2018 ◽  
Vol 142 ◽  
pp. 1-10 ◽  
Author(s):  
Kuheli Mondal (Das) ◽  
Saurav Das ◽  
Aminudin Bin Hj Abu ◽  
Nozomu Hamada ◽  
Hoong Thiam Toh ◽  
...  

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