Affine Combination of the Filtered-x LMS/F Algorithms for Active Control

Pradhan, S; Qiu, X; Ji, J

Affine Combination of the Filtered-x LMS/F Algorithms for Active Control

Pradhan, S

Qiu, X

Ji, J

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Publisher:: Springer
Publication Type:: Conference Proceeding
Citation:: Vibration Engineering for a Sustainable Future: Active and Passive Noise and Vibration Control,, 2021, 1, pp. 313-320
Issue Date:: 2021-01-01

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Field	Value	Language
dc.contributor.author	Pradhan, S https://orcid.org/0000-0002-7463-0932
dc.contributor.author	Qiu, X https://orcid.org/0000-0002-5181-1220
dc.contributor.author	Ji, J https://orcid.org/0000-0003-3280-5463
dc.date	2019-11-18
dc.date.accessioned	2022-06-29T08:15:43Z
dc.date.available	2022-06-29T08:15:43Z
dc.date.issued	2021-01-01
dc.identifier.citation	Vibration Engineering for a Sustainable Future: Active and Passive Noise and Vibration Control,, 2021, 1, pp. 313-320
dc.identifier.isbn	978-3-030-47617-5
dc.identifier.uri	http://hdl.handle.net/10453/158465
dc.description.abstract	The filtered-x least mean square algorithm is extensively employed for active control, which exhibits a trade-off between convergence speed and the steady-state control performance. In this paper, an affine combination strategy of the filtered-x least mean square and fourth algorithms is proposed, which can be regarded as a generalized convex combination. Unlike the convex combination, the combining parameter in this linear combination is not constrained to lie in a specific interval and plays a vital role in deciding the overall system performance. An adaptation rule is developed for updating the combining parameter. The proposed affine combination strategy is used to control white noise and multitone noise. The simulation results demonstrate that the proposed algorithm provides faster convergence and improved steady-state control performance. Furthermore, the proposed affine combination is also robust with an imperfect secondary path model.
dc.language	en
dc.publisher	Springer
dc.relation.ispartof	Vibration Engineering for a Sustainable Future: Active and Passive Noise and Vibration Control,
dc.relation.ispartof	Asia-Pacific Vibration Conference
dc.relation.isbasedon	10.1007/978-3-030-47618-2_39
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Affine Combination of the Filtered-x LMS/F Algorithms for Active Control
dc.type	Conference Proceeding
utslib.citation.volume	1
utslib.location.activity	Australia
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2022-06-29T08:15:34Z
pubs.finish-date	2019-11-20
pubs.place-of-publication	Switzerland
pubs.publication-status	Published
pubs.start-date	2019-11-18
pubs.volume	1
dc.location	Switzerland

Abstract:

The filtered-x least mean square algorithm is extensively employed for active control, which exhibits a trade-off between convergence speed and the steady-state control performance. In this paper, an affine combination strategy of the filtered-x least mean square and fourth algorithms is proposed, which can be regarded as a generalized convex combination. Unlike the convex combination, the combining parameter in this linear combination is not constrained to lie in a specific interval and plays a vital role in deciding the overall system performance. An adaptation rule is developed for updating the combining parameter. The proposed affine combination strategy is used to control white noise and multitone noise. The simulation results demonstrate that the proposed algorithm provides faster convergence and improved steady-state control performance. Furthermore, the proposed affine combination is also robust with an imperfect secondary path model.

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http://hdl.handle.net/10453/158465