The popular filtered-x least-mean squares (FxLMS) algorithm has been widely adopted in active noise control (ANC) for relatively stationary disturbances. The convergence behavior of the FxLMS algorithm has been well understood in the adaptation process for stationary sinusoidal or stochastic white noises. Its behavior for transient impulses has not received as much attention. This paper employs the root locus theory to develop a graphical tool for the analysis and design of the adaptive ANC system for repetitive impulses. It is found that there is a dominant pole controlling the stability of the adaptation process, in which the maximum step size can be determined. The analysis also observes a transient adaptation behavior in the FxLMS algorithm for repetitive impulses. In this case, the predicted step-size bound decreases as the number of repetitive impulses increases for a general secondary path. Furthermore, the dominant root tuning process is applied by incorporating a digital filter after the output of the adaptive controller, which significantly increases the step-size bound. The accuracy of the analysis was extensively validated by numerical simulation studies by assuming various secondary path models. The simulated results show an excellent agreement with analytical predictions.

References

1.
Kuo
,
S. M.
, and
Morgan
,
D. R.
,
1999
, “
Active Noise Control: A Tutorial Review
,”
Proc. IEEE
,
87
(
6
), pp.
943
973
.
2.
Elliott
,
S. J.
,
2008
, “
A Review of Active Noise and Vibration Control in Road Vehicles
,” ISVR Technical Memorandum No. 981.
3.
Shao
,
M.
, and
Nikias
,
C. L.
,
1993
, “
Signal Processing With Fractional Lower Order Moments: Stable Processes and Their Applications
,”
Proc. IEEE
,
81
(
7
), pp.
986
1010
.
4.
Zhou
,
Y.
,
Zhang
,
Q.
, and
Yin
,
Y.
,
2015
, “
Active Control of Impulsive Noise With Symmetric α-Stable Distribution Based on an Improved Step-Size Normalized Adaptive Algorithm
,”
Mech. Syst. Signal Process.
,
56–57
, pp.
320
339
.
5.
Sun
,
G.
,
Li
,
M.
, and
Lim
,
T. C.
,
2015
, “
Enhanced Filtered-x Least Mean M-Estimate Algorithm for Active Impulsive Noise Control
,”
Appl. Acoust.
,
90
, pp.
31
41
.
6.
Wu
,
L.
,
Qiu
,
X.
,
Burnett
,
I. S.
, and
Guo
,
Y.
,
2015
, “
A Recursive Least Square Algorithm for Active Control of Mixed Noise
,”
J. Sound Vib.
,
339
, pp.
1
10
.
7.
Akhtar
,
M. T.
,
2014
, “
Binormalized Data-Reusing Filtered-Reference Algorithm for Impulsive Active Noise Control
,”
IEEE 57th International Midwest Symposium on Circuits and Systems (MWSCAS)
, College Station, TX, Aug. 3–6, pp.
691
694
.
8.
Wu
,
L. F.
, and
Qiu
,
X. J.
,
2013
, “
Active Impulsive Noise Control Algorithm With Post Adaptive Filter Coefficient Filtering
,”
IET Signal Process.
,
7
(
6
), pp.
515
521
.
9.
Wu
,
L.
,
He
,
H.
, and
Qiu
,
X.
,
2011
, “
An Active Impulsive Noise Control Algorithm With Logarithmic Transformation
,”
IEEE Trans. Audio, Speech, Lang. Process.
,
19
(
4
), pp.
1041
1044
.
10.
Hansen
,
C.
, and
Snyder
,
S.
,
1997
,
Active Control of Noise and Vibration
,
E&FN Spon
,
London
.
11.
Sun
,
G.
,
Feng
,
T.
,
Li
,
M.
, and
Lim
,
T. C.
,
2015
, “
Convergence Analysis of FxLMS-Based Active Noise Control for Repetitive Impulses
,”
Appl. Acoust.
,
89
, pp.
178
187
.
12.
Glover
,
J. R.
,
1977
, “
Adaptive Noise Canceling Applied to Sinusoidal Interferences
,”
IEEE Trans. Acoust. Speech
,
25
(
6
), pp.
484
491
.
13.
Elliott
,
S. J.
,
Stothers
, I
. M.
, and
Nelson
,
P. A.
,
1987
, “
A Multiple Error LMS Algorithm and Its Application to the Active Control of Sound and Vibration
,”
IEEE Trans. Acoust. Speech
,
35
(
10
), pp.
1423
1434
.
14.
Vicente
,
L.
, and
Masgrau
,
E.
,
2002
, “
Analysis of LMS Algorithm With Delayed Coefficient Adaptation for Sinusoidal Reference
,”
European Signal Processing Conference
, pp.
1
4
.
15.
Vicente
,
L.
,
2006
, “
Novel FxLMS Convergence Condition With Deterministic Reference
,”
IEEE Trans. Signal Process.
,
54
(
10
), pp.
3768
3774
.
16.
Xiao
,
Y. G.
,
Ikuta
,
A.
,
Ma
,
L. Y.
, and
Khorasani
,
K.
,
2008
, “
Stochastic Analysis of the FXLMS-Based Narrowband Active Noise Control System
,”
IEEE Trans. Audio Speech
,
16
(
5
), pp.
1000
1014
.
17.
Long
,
G.
,
Ling
,
F.
, and
Proakis
,
J. G.
,
1989
, “
The Lms Algorithm With Delayed Coefficient Adaptation
,”
IEEE Trans. Acoust. Speech
,
37
(
9
), pp.
1397
1405
.
18.
Bjarnason
,
E.
,
1995
, “
Analysis of the Filtered-x Lms Algorithm
,”
IEEE Trans. Speech Audio Process.
,
3
(
6
), pp.
504
514
.
19.
Ardekani
,
I. T.
, and
Abdulla
,
W. H.
,
2012
, “
Root Locus Analysis and Design of the Adaptation Process in Active Noise Control
,”
J. Acoust. Soc. Am.
,
132
(
4
), pp.
2313
2324
.
20.
Ardekani
,
I. T.
, and
Abdulla
,
W. H.
,
2012
, “
Effects of Imperfect Secondary Path Modeling on Adaptive Active Noise Control Systems
,”
IEEE Trans. Control Syst. Technol.
,
20
(
5
), pp.
1252
1262
.
21.
Ardekani
,
I. T.
, and
Abdulla
,
W.
,
2011
, “
FxLMS-Based Active Noise Control: A Quick Review
,”
Asia Pacific Signal and Information Processing Association Annual (APSIPA) Summit and Conference
, Xi'an, China.
22.
Ardekani
,
I. T.
, and
Abdulla
,
W. H.
,
2011
, “
Filtered Weight FxLMS Adaptation Algorithm: Analysis, Design and Implementation
,”
Int. J. Adapt. Control
,
25
(
11
), pp.
1023
1037
.
23.
Ardekani
,
I. T.
, and
Abdulla
,
W. H.
,
2011
, “
On the Convergence of Real-Time Active Noise Control Systems
,”
Signal Process.
,
91
(
5
), pp.
1262
1274
.
24.
Ardekani
,
I. T.
, and
Abdulla
,
W. H.
,
2011
, “
On the Stability of Adaptation Process in Active Noise Control Systems
,”
J. Acoust. Soc. Am.
,
129
(
1
), pp.
173
184
.
25.
Ardekani
,
I. T.
, and
Abdulla
,
W. H.
,
2010
, “
Theoretical Convergence Analysis of FxLMS Algorithm
,”
Signal Process.
,
90
(
12
), pp.
3046
3055
.
26.
Shinaishin
,
O. A.
,
1974
, “
Impact-Induced Industrial Noise
,”
Noise Control Eng.
,
2
(
1
), pp.
30
36
.
27.
Dym
,
C. L.
,
1977
, “
Sources of Industrial Impact/Impulsive Noise
,”
Noise Control Eng.
,
8
(
2
), pp.
81
87
.
28.
Zhou
,
Y.
,
Yin
,
Y.
, and
Zhang
,
Q.
,
2013
, “
Active Control of Repetitive Impulsive Noise in a Non-Minimum Phase System Using an Optimal Iterative Learning Control Algorithm
,”
J. Sound Vib.
,
332
(
18
), pp.
4089
4102
.
29.
Pinte
,
G.
,
Boonen
,
R.
,
Desmet
,
W.
, and
Sas
,
P.
,
2009
, “
Active Structural Acoustic Control of Repetitive Impact Noise
,”
J. Sound Vib.
,
319
(
3–5
), pp.
768
794
.
30.
Kuo
,
S. M.
, and
Morgan
,
D. R.
,
1995
,
Active Noise Control Systems: Algorithms and DSP Implementations
,
Wiley
,
New York
.
You do not currently have access to this content.