Title page for ETD etd-32898-121223

Type of Document

Dissertation

Author

Cabell, Randolph H. III

Author's Email Address

r.h.cabell@larc.nasa.gov

URN

etd-32898-121223

Title

A Principal Component Algorithm for Feedforward Active Noise and Vibration Control

Degree

Doctor of Philosophy

Department

Mechanical Engineering

Advisory Committee

Advisor Name	Title
Chris Fuller	Committee Chair
Dr. Alfred Wicks	Committee Member
Dr. Ricardo Burdisso	Committee Member
Dr. Richard Silcox	Committee Member
Dr. William Baumann	Committee Member

Keywords

active control
aircraft interior noise
principal component analysis

Date of Defense

1998-04-17

Availability

unrestricted

Abstract

A principal component least mean square
(PC-LMS) adaptive algorithm is described that has considerable
benefits for large control systems used to implement feedforward
control of single frequency disturbances. The algorithm is a
transform domain version of the multichannel filtered-x LMS algorithm.
The transformation corresponds to the principal components of the
transfer function matrix between the sensors and actuators in a
control system at a single frequency. The method is similar to other
transform domain LMS algorithms because the transformation can be used
to accelerate convergence when the control system is ill-conditioned.
This ill-conditioning is due to actuator and sensor placement on a
continuous structure. The principal component transformation rotates
the control filter coefficient axes to a more convenient coordinate
system where (1) independent convergence factors can be used on each
coordinate to accelerate convergence, (2) insignificant control
coordinates can be eliminated from the controller, and (3) coordinates
that require excessive control effort can be eliminated from the
controller. The resulting transform domain algorithm has lower
computational requirements than the filtered-x LMS algorithm. The
formulation of the algorithm given here applies only to single
frequency control problems, and computation of the decoupling
transforms requires an estimate of the transfer function matrix
between control actuators and error sensors at the frequency of
interest. The feasibility of the method was demonstrated in real-time
noise control experiments involving 48 microphones and 12 control
actuators mounted on a closed cylindrical shell. Convergence of the
PC-LMS algorithm was more stable than the filtered-x LMS algorithm.
In addition, the PC-LMS controller produced more noise reduction with
less control effort than the filtered-x LMS controller in several
tests.

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