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Abstract

Vibrating plates have been recently used for a number of active noise control applications. They are resistant to difficult environmental conditions including dust, humidity, and even precipitation. However, their properties significantly depend on temperature. The plate temperature changes, caused by ambient temperature changes or plate heating due to internal friction, result in varying response of the plate, and may make it significantly different than response of a fixed model. Such mismatch may deteriorate performance of an active noise control system or even lead to divergence of a model-based adaptation algorithm.

In this paper effects of vibrating plate temperature variation on a feedforward adaptive active noise reduction system with the multichannel Filtered-reference LMS algorithm are examined. For that purpose, a thin aluminum plate is excited with multiple Macro-Fiber Composite actuators. The plate temperature is forced by a set of Peltier cells, what allows for both cooling and heating the plate. The noise is generated at one side of the plate, and a major part of it is transmitted through the plate. The goal of the control system is to reduce sound pressure level at a specified area on the other side of the plate.

To guarantee successful operation of the control system in face of plate temperature variation, a gain-scheduling scheme is proposed to support the Filtered-reference LMS algorithm.

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Authors and Affiliations

Krzysztof Mazur
Marek Pawełczyk
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Abstract

In the areas of acoustic research or applications that deal with not-precisely-known or variable conditions, a method of adaptation to the uncertainness or changes is usually necessary. When searching for an adaptation algorithm, it is hard to overlook the least mean squares (LMS) algorithm. Its simplicity, speed of computation, and robustness has won it a wide area of applications: from telecommunication, through acoustics and vibration, to seismology. The algorithm, however, still lacks a full theoretical analysis. This is probabely the cause of its main drawback: the need of a careful choice of the step size - which is the reason why so many variable step size flavors of the LMS algorithm has been developed.

This paper contributes to both the above mentioned characteristics of the LMS algorithm. First, it shows a derivation of a new necessary condition for the LMS algorithm convergence. The condition, although weak, proved useful in developing a new variable step size LMS algorithm which appeared to be quite different from the algorithms known from the literature. Moreover, the algorithm proved to be effective in both simulations and laboratory experiments, covering two possible applications: adaptive line enhancement and active noise control.

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Authors and Affiliations

Dariusz Bismor
ORCID: ORCID

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