2013Unpublished venueRequires access

Adaptive active noise control in free space

Iman Ardekani, Waleed H. Abdulla

Open publisher page 1 citations

Abstract

This paper develops a reliable methodology for active control of acoustic noise in free space. The core of this paper consists of a root locus analysis on the adaptation process performed in active noise control. Based on this analysis, a novel active noise control algorithm is derived. This algorithm is fully implemented in an experimental setup. Different experiments with this setup show that the traditional active noise control algorithm is not stable when the setup is used in free space. However, the proposed algorithm is stable and converges at a high convergence rate until the noise level is reduced by 15 dB in steady-state conditions.

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What this paper is about

This paper develops a reliable methodology for active control of acoustic noise in free space. The core of this paper consists of a root locus analysis on the adaptation process performed in active noise control. Based on this analysis, a novel active noise control algorithm is derived. This algorithm is fully implemented in an experimental setup. Different experiments with this setup show that the traditional active noise control algorithm is not stable when the setup is used in free space. However, the proposed algorithm is stable and converges at a high convergence rate until the noise level is reduced by 15 dB in steady-state conditions.

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Available abstract

This paper develops a reliable methodology for active control of acoustic noise in free space. The core of this paper consists of a root locus analysis on the adaptation process performed in active noise control. Based on this analysis, a novel active noise control algorithm is derived. This algorithm is fully implemented in an experimental setup. Different experiments with this setup show that the traditional active noise control algorithm is not stable when the setup is used in free space. However, the proposed algorithm is stable and converges at a high convergence rate until the noise level is reduced by 15 dB in steady-state conditions.

Key concepts: Active noise control, Root locus, Noise (video), Computer science, Control theory (sociology), Convergence (economics), Noise measurement, Adaptive control

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