.

1. Remote FxLMS Algorithm for Active Control
of Sound in Remote Locations
Iman Ardekani
Department of Computing
Unitec Institute of Technology
Auckland, New Zealand
Waleed Abdulla
ECE Department
The University of AUckland
Auckland, New Zealand
APSIPA ASC 2014
APSIPA Annual Summit and Conference
Cambodia, Dec. 9 – 12, 2014

2. Outline
• ANC
• ANC Analysis in Acoustic Domain
• Remote ANC
• Adaptive Remote ANC Algorithm
• Results
• Conclusion
2
2

3. Active Noise Control – Why?
𝜆
𝜆 =
𝑐
𝑓
wave length (m) sound velocity (m/s)
frequency (Hz)
𝑑
effective passive control 𝑑 ≫ 𝜆
𝑓 (𝐻𝑧) 𝜆 (𝑚)
10000 0.0343
1000 0.343
100 3.343
Passive noise control is
bulky and costly for low
frequencies!
3

4. Active Noise Control – Original Idea
4
Primary Noise
Secondary Noise
Residual noise

5. Active Noise Control – Acoustic Domain
5
u(n) : original noise
d(n) : primary noise
Reference
mic
Error
mic
d’(n) : secondary noise
v(n) : anti noise d(n)  u(n)
d’(n) v(n)
e(n)
u(n) v(n)
e(n)
Control
System
Control
System

6. Active Noise Control – Digital Electronic Domain
6
W
Gu(n) e(n)
FxLMS
H
v(n)
Control System
d(n)
d'(n)
Minimization of e(n) power through producing v(n) using u(n) and e(n)
FxLMS
Algorithm

7. Active Noise Control – Research Gap
7
𝜆
20
Traditional ANC
e(n)
Problems:
- very small zone of quiet
- space occupied by the error mic
10 dB ZoQ
𝜆
20
e(n)
10 dB ZoQ
Advantage:
- effective use of space in quiet zone
Remote ANC (proposed)

8. ANC Analysis in Acoustic Domain – Coordinate System
8
u(n)
Reference mic
v(n)
L1
e(n)
Control Source
L2 Lo
Error mic (ZoQ centre)
W
G e(n)
FxLMS
Update Eq
H
+
v(n)
Digital control domain
Physical domain
z-axis
L1
L0 L2
is

9. ANC Analysis in Acoustic Domain – Propagation
9
L1
z-axis
y-axisϕ
1
d
D
L1
L2L0
z-axis
y-axisϕ
1
d
D
L1
L2L0
ϕr
Lr
ϕr
u(n)
v(n)
W
Gu(n) e(n)
FxLMS
H
+
v(n)
Digital control domain
Physical domain

10. Remote Active Noise Control
10
Remote location
D
L1
z-axis
y-axisϕ
1
d
D
L1
L2L0
ϕr
Lr
ϕr

11. Remote Active Noise Control
11 L1
z-axis
y-axisϕ
1
d
D
L1
L2L0
z-axis
y-axisϕ
1
d
D
L1
L2L0
ϕr
Lr
ϕr

12. Remote Active Noise Control
12
L1
L0 L2
z-axis
y-axisϕ
1
d
D
L1
L2L0
z-axis
y-axisϕ
1
d
D
L2L0
ϕr
Lr
ϕr
y-axisϕ
1
d
D
L1
L2L0
z-axis
y-axisϕ
1
d
D
L1
L2L0
ϕr
Lr
ϕr
Traditional ANC Remote ANC

13. Remote Active Noise Control
13
Traditional ANC Remote ANC
W
Gu(n) e(n)
FxLMS
H
+
v(n)
Digital control domain
Physical domain
z-axis
L1
L0 L2
z-axis
Krz
Gu(n) e(n)
Remote
FxLMS
H
v(n)
W
a(n) -ϕr
Digital control domain
+
Physical domain

14. Remote Active Noise Control
14
Traditional ANC Remote ANC
W
Gu(n) e(n)
FxLMS
H
+
v(n)
Digital control domain
Physical domain
z-axis
L1
L0 L2
z-axis
Krz
Gu(n) e(n)
Remote
FxLMS
H
v(n)
W
a(n) -ϕr
Digital control domain
+
Physical domain

15. Results
Page 15
r
z-axis
y-axis70o
0.5m
L1
L2L0
Lr
10 20 30 40 50 60
−0.5
0
0.5
1
n
f1
(n)
0 10 20 30 40 50 60
−0.5
0
0.5
1
n
f2
(n)

16. Results
Page 16

17. Results
Page 17

18. Conclusion
• A novel model for the analysis of the ANC systems in
the acoustic domain is proposed.
• Based on this model, a methodology for active noise
control in remote location is developed.
• An adaptive framework for the realization of the
proposed remote ANC system is developed.
• Using remote ANC idea, the space available in the
quiet zone can be used more effectively.
• Future work: targeting 3D zones of quiet in remote
locations instead of a point.
Page 18
𝜆
20
e(n)
10 dB ZoQ