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Robust performance of virtual sensing methods for active noise control

Robust performance of virtual sensing methods for active noise control
Robust performance of virtual sensing methods for active noise control
This paper investigates the effect of changes in the environment on the performance of two widely-used virtual sensing methods for active noise control (ANC): the remote-microphone method and the additional-filter method. Robust performance of adaptive feedforward control algorithms incorporating such virtual sensing techniques is essential to achieving noise attenuation at the designated locations in practice, when subject to uncertainties in the control environment. Off-line simulations using the data measured with a headrest ANC system in a running car are initially conducted, to evaluate the performance of the two virtual sensing methods under practical conditions. The differences between the two methods are further studied by using an analytical model and numerical simulations of the headrest ANC system. It is shown that in general the additional-filter method is sensitive to uncertainties in the properties of the reference signals used for feedforward control, whereas the remote-microphone method is sensitive to changes in the plant responses related to the monitoring microphones. This study, therefore, can be used to guide the choice of virtual sensing methods in different applications.
Active noise control, In-car measurement, Robust performance, Virtual sensing
0888-3270
Zhang, Jin
4cb1ed20-f74c-4b0c-a3aa-29761b0640b7
Elliott, Stephen
721dc55c-8c3e-4895-b9c4-82f62abd3567
Cheer, Jordan
8e452f50-4c7d-4d4e-913a-34015e99b9dc
Zhang, Jin
4cb1ed20-f74c-4b0c-a3aa-29761b0640b7
Elliott, Stephen
721dc55c-8c3e-4895-b9c4-82f62abd3567
Cheer, Jordan
8e452f50-4c7d-4d4e-913a-34015e99b9dc

Zhang, Jin, Elliott, Stephen and Cheer, Jordan (2021) Robust performance of virtual sensing methods for active noise control. Mechanical Systems and Signal Processing, 152, [107453]. (doi:10.1016/j.ymssp.2020.107453).

Record type: Article

Abstract

This paper investigates the effect of changes in the environment on the performance of two widely-used virtual sensing methods for active noise control (ANC): the remote-microphone method and the additional-filter method. Robust performance of adaptive feedforward control algorithms incorporating such virtual sensing techniques is essential to achieving noise attenuation at the designated locations in practice, when subject to uncertainties in the control environment. Off-line simulations using the data measured with a headrest ANC system in a running car are initially conducted, to evaluate the performance of the two virtual sensing methods under practical conditions. The differences between the two methods are further studied by using an analytical model and numerical simulations of the headrest ANC system. It is shown that in general the additional-filter method is sensitive to uncertainties in the properties of the reference signals used for feedforward control, whereas the remote-microphone method is sensitive to changes in the plant responses related to the monitoring microphones. This study, therefore, can be used to guide the choice of virtual sensing methods in different applications.

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Manuscript_MSSP20-971_Draft_v2 - Accepted Manuscript
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More information

Accepted/In Press date: 10 November 2020
e-pub ahead of print date: 28 November 2020
Published date: 1 May 2021
Keywords: Active noise control, In-car measurement, Robust performance, Virtual sensing

Identifiers

Local EPrints ID: 445527
URI: http://eprints.soton.ac.uk/id/eprint/445527
ISSN: 0888-3270
PURE UUID: 46b551ee-193e-4a3c-9619-0c9e8117c904
ORCID for Jordan Cheer: ORCID iD orcid.org/0000-0002-0552-5506

Catalogue record

Date deposited: 14 Dec 2020 17:32
Last modified: 17 Mar 2024 06:08

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Contributors

Author: Jin Zhang
Author: Stephen Elliott
Author: Jordan Cheer ORCID iD

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