Adaptive even mirror Fourier filtered error LMS algorithm for multichannel nonlinear active noise control

Abstract Active Noise Control (ANC) of noise transmitted through a vibrating plate causes many problems not observed in classical ANC using loudspeakers. They are mainly due to vibrations of a not ideally clamped plate and use of nonlinear actuators, like MFC patches. In case of noise transmission though a plate, nonlinerities exist in both primary and secondary paths. Existence of nonlinerities in the system may degrade performance of a linear feedforward control system usually used for ANC. The performance degradation is especially visible for simple deterministic noise, such as tonal noise, where very high reduction is expected. Linear feedforward systems in such cases are unable to cope with higher harmonics generated by the nonlinearities. Moreover, nonlinearities, if not properly tackled with, may cause divergence of an adaptive control system. In this paper a feedforward ANC system reducing sound transmitted through a vibrating plate is presented. The ANC system uses nonlinear control filters to suppress negative effects of nonlinearies in the system. Filtered-error LMS algorithm, found more suitable than usually used Filtered-reference LMS algorithm, is employed for updating parameters of the nonlinear filters. The control system is experimentally verified and obtained results are discussed.

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Experiments in Filtered X-LMS Algorithm for Active Noise Control in Ducts

10.26678/abcm.cobem2019.cob2019-1991 ◽

2019 ◽

Author(s):

Renan Benitz ◽

Herbert Gomes

Keyword(s):

Noise Control ◽

Active Noise Control ◽

Lms Algorithm ◽

Active Noise

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

Applied Sciences ◽

10.3390/app11010344 ◽

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.

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Improved stability performance of a feedback active noise control using a Steiglitz-McBride adaptive notch filter and robust secondary path identification based on variable step size Griffiths LMS algorithm

Noise Control Engineering Journal ◽

10.3397/1/376914 ◽

2021 ◽

Vol 69 (2) ◽

pp. 136-145

Author(s):

S. Roopa ◽

S.V. Narasimhan

Keyword(s):

Noise Control ◽

Active Noise Control ◽

Notch Filter ◽

Lms Algorithm ◽

Variable Step Size ◽

Step Size ◽

Adaptive Notch Filter ◽

Active Noise ◽

Variable Step ◽

Feedback Active Noise Control

A stable feedback active noise control (FBANC) system with an improved performance in a broadband disturbance environment is proposed in this article. This is achieved by using a Steiglitz-McBride adaptive notch filter (SM-ANF) and robust secondary path identification (SPI) both based on variable step size Griffiths least mean square (LMS) algorithm. The broadband disturbance severely affects not only FBANC input synthesized but also the SPI.TheSM-ANFestimated signal has narrowband component that is utilized for the FBANC input synthesis. Further, the SM-ANF error has broadband component utilized to get the desired signal for SPI. The use of variable step size Griffiths gradient LMS algorithm for SPI enables the removal of broadband disturbance and non-stationary disturbance from the available desired signal for better SPI. For a narrowband noise field, the proposed FBANC improves the convergence rate significantly (20 times) and the noise reduction from 10 dB to 15 dB (50%improvement) over the conventional FBANC (without SM-ANF and variable step size Griffiths LMS adaptation for SPI).

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