A rapid prototyping system for broadband multichannel active noise and vibration control

Wesselink, J.M.

doi:10.3990/1.9789036529365

Cited by 2 publications

(2 citation statements)

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“…A SISO version of the algorithm was implemented on a Real Time Linux platform, of which the details can be found in Ref. [18]. The algorithm was tested in an experiment in which the goal was to minimize the acoustic pressure at the right hand side of a duct, caused by a white noise source on the left hand side of a duct.…”

Section: Resultsmentioning

confidence: 99%

Multi-channel Kalman filters for active noise control

Ophem

Berkhoff

2013

The Journal of the Acoustical Society of America

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By formulating the feed-forward broadband active noise control problem as a state estimation problem it is possible to achieve a faster rate of convergence than the filtered reference least mean squares algorithm and possibly also a better tracking performance. A multiple input/multiple output Kalman algorithm is derived to perform this state estimation. To make the algorithm more suitable for real-time applications, the Kalman filter is written in a fast array form and the secondary path state matrices are implemented in output normal form. The resulting filter implementation is tested in simulations and in real-time experiments. It was found that for a constant primary path the filter has a fast rate of convergence and is able to track changes in the frequency spectrum. For a forgetting factor equal to unity the system is robust but the filter is unable to track rapid changes in the primary path. A forgetting factor lower than 1 gives a significantly improved tracking performance but leads to a numerical instability for the fast array form of the algorithm.

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Section: Resultsmentioning

confidence: 99%