scholarly journals Active noise control for periodic disturbances

2001 ◽  
Vol 9 (1) ◽  
pp. 200-205 ◽  
Author(s):  
M. Bodson ◽  
J.S. Jensen ◽  
S.C. Douglas
Keyword(s):  
Noise Control ◽  
Active Noise Control ◽  
Periodic Disturbances ◽  
Active Noise

scholarly journals Modified Filtered-X Hierarchical LMS Algorithm with Sequential Partial Updates for Active Noise Control

2020 ◽  
Vol 11 (1) ◽  
pp. 344
Author(s):  
Pedro Ramos Lorente ◽  
Raúl Martín Ferrer ◽  
Fernando Arranz Martínez ◽  
Guillermo Palacios-Navarro
Keyword(s):  
Computational Complexity ◽  
Convergence Rate ◽  
Noise Control ◽  
Active Noise Control ◽  
Adaptive Strategy ◽  
Lms Algorithm ◽  
Step Size ◽  
Periodic Disturbances ◽  
Active Noise ◽  
Dependent Parameter

In the field of active noise control (ANC), a popular method is the modified filtered-x LMS algorithm. However, it has two drawbacks: its computational complexity higher than that of the conventional FxLMS, and its convergence rate that could still be improved. Therefore, we propose an adaptive strategy which aims at speeding up the convergence rate of an ANC system dealing with periodic disturbances. This algorithm consists in combining the organization of the filter weights in a hierarchy of subfilters of shorter length and their sequential partial updates (PU). Our contribution is threefold: (1) we provide the theoretical basis of the existence of a frequency-dependent parameter, called gain in step-size. (2) The theoretical upper bound of the step-size is compared with the limit obtained from simulations. (3) Additional experiments show that this strategy results in a fast algorithm with a computational complexity close to that of the conventional FxLMS.

Simulations of an Internal Model-Based Active Noise Control System for Suppressing Periodic Disturbances

1998 ◽  
Vol 120 (1) ◽  
pp. 111-116 ◽  
Author(s):  
Mingsian R. Bai ◽  
Tenyau Wu
Keyword(s):  
Internal Model ◽  
Noise Control ◽  
Active Noise Control ◽  
Robust Stabilization ◽  
Internal Model Principle ◽  
Model Based ◽  
Periodic Disturbances ◽  
System A ◽  
Active Noise ◽  
Infinite Loop

This study proposes an active noise control algorithm using the internal model principle. The structure of the noise is built in the transfer function of the controller in the unity feedback configuration. This method is particularly effective in suppressing periodic disturbance in spite of its simplicity. Perfect disturbance rejection at selected frequencies is achieved by the infinite loop gain of the system. A simulation was performed to investigate the internal model-based algorithm. The guidelines of choosing the control parameters with reference to a robust stabilization theory are summarized.

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