Virtual Sensing (VS) is considered to be an extension for feedforward Active Noise and Vibration Control (ANVC) systems when, for example, it is desired to minimize the response at one or more spatial locations where it is either physically impossible or undesirable to place an actual error sensor. In this context, VS is an estimation technique for predicting the appropriate system response using available measurements and a dynamic system model. A hybrid adaptive feedforward observer is proposed which has the ability to overcome the limitations of conventional dynamic observer designs. The hybrid observer utilizes a conventional dynamic observer augmented with an adaptive feedforward element for estimating the effect of the persistent disturbance. For simplicity, we restrict this development to a single tonal disturbance for which a coherent reference is assumed available. It will be appreciated that this technique may be extended to handle disturbances that contain multiple tones as well as broadband noise, as long as suitable reference signals are available. Numerical simulations and real-time experiments were performed on a one-dimensional acoustic duct. The results demonstrate that the hybrid adaptive feedforward observer is an effective method for predicting the virtual sensor response in an ANVC system.

Issue Section:
Technical Papers
Keywords:
active noise control, vibration control, feedforward, adaptive control, observers
Topics:
Ducts, Errors, Feedforward control, Sensors, Signals, Dynamic systems, Noise (Sound), Acoustics, Vibration control, Computer simulation
1.
Fuller, C. R., Elliott, S. J., and Nelson, P. A., 1996, Active Control of Vibration, Academic Press, London.
2.
Kuo, S. M., and Morgan, D. R., 1996, ActiveNoise Control Systems, Wiley, New York.
3.
Nelson, P. A., and Elliott, S. J., 1992, Active Control of Sound, Academic Press, London.
4.
Elliott, S. J., 1995, “Active Sound Control Systems and Sound Reproduction Systems,” U.S. Patent, Jan. 10, No. 5,381,485.
5.
Garcia-Bonito, J., Elliott, S. J., and Boucher, C. C., 1996, “A Virtual Microphone Arrangement in a Practical Active Headrest,” Proceedings of Internoise 96, pp. 1115–1120.
6.
Popovich, S. R., 1997, “Active Acoustic Control In Remote Regions,” U.S. Patent, Dec. 23, No. 5,701,305.
7.
Kammer
,
D. C.
,
1997
, “
Estimation of Structural Response Using Remote Sensor Locations
,”
J. Guid. Control Dyn.
,
20
, No.
3
, May–June, pp.
501
–
508
.
8.
Tran, C. M., 1998, “A Hybrid Adaptive Feedforward Observer for Virtual Sensing,” Ph.D. dissertation, North Carolina State University, Raleigh, NC.
9.
Brogan, W. L., 1991, Modern Control Theory, 3rd Edition, Prentice-Hall, Englewood Cliffs, NJ.
10.
Messner
,
W.
, and
Bodson
,
M.
,
1995
, “
Design of Adaptive Feedforward Algorithms Using Internal Model Equivalence
,”
Int. Journal of Adaptive Control and Signal Proc.
,
9
, pp.
199
–
212
.
11.
Franklin, G. F., Powell, J. D., and Emami-Naeini, A., 1994, Feedback Control of Dynamic Systems, 3rd edition, Addison-Wesley, Reading, MA.
12.
Davison
,
E. J.
,
1976
, “
The Robust Control of a Servomechanism Problem for Linear Time-Invariant Multivariable Systems
,”
IEEE Trans. Autom. Control
,
AC-21
, February, No. 1.
13.
Kwakernaak, H., and Sivan, R., 1972, Linear Optimal Control Systems, Wiley-Interscience, NY.
14.
Douglas, S. C., and Olkin, J. A., 1993, “Multiple-input, Multiple-output, Multiple-error Adaptive Feedforward Control Using the Filtered-X Normalized LMS Algorithm,” Proc. 2nd Conf. on Recent Advances in Active Control of Sound and Vibration, Blacksburg, VA, April, pp. 743–754.
15.
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, Signal Process.
,
ASSP-35
, Oct., No.
10
, pp.
1423
–
1434
.
16.
Popovich, S. R., 1997, “Adaptive Tonal Control System with Constrained Output and Adaptation,” U.S. Patent, May 27, No. 5,633,795.
17.
Southward, S. C., Heath, M. C., and Ferguson, M. K., 1995, “A Hybrid LMS Implementation for Tonal Noise Cancellation,” Active 95, Newport Beach, CA, July, pp. 1067–1078.
18.
ACX™, 1995, SmartID System Identification Software, Active Control eXperts, Inc., Cambridge, MA.
19.
Widrow, Bernard, and Stearns, S. D., 1985, Adaptive Signal Processing, Prentice-Hall, Englewood Cliffs, NJ.
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