Convergence analysis of the Filtered-U LMS algorithm for active noise control in case perfect cancellation is not possible
article
The Filtered-U LMS algorithm, proposed by Eriksson for active noise control applications, adapts the coefficients of an infinite-impulse response controller. Conditions for global convergence of the Filtered-U LMS algorithm were presented by Wang and Ren (Signal Processing, 73 (1999) 3) and Mosquera and Pérez-González (Signal Processing, 80 (2000) 5) for the case where perfect noise cancellation is achievable, which means only measurement noise remains. This paper shows that the assumption of perfect cancellation is not necessary. In real situations perfect cancellation is often not achievable due to delays and non-minimum phase zeros. The conclusion is derived by analysis of the structure of the Wiener optimal solution. This also leads to the suggestion of preconditioning filters in the Filtered-U LMS updating. The preconditioning has shown considerable increase of the convergence rate in a realistic simulation study.
Topics
TNO Identifier
237130
ISSN
01651684
Source
Signal Processing, 83(6), pp. 1239-1254.
Publisher
Elsevier
Place of publication
Amsterdam
Pages
1239-1254
Files
To receive the publication files, please send an e-mail request to TNO Repository.