Active Disturbance Cancellation - In Nonlinear Dynamical Systems Using Neural Networks

by Canfield, John
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Canfield, John Active Disturbance Cancellation - In Nonlinear Dynamical Systems Using Neural Networks
Canfield, John - Active Disturbance Cancellation - In Nonlinear Dynamical Systems Using Neural Networks

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Description

This book begins with a brief background on the
field of active disturbance cancellation with a
particular focus on the challenges of acoustic
cancellation environments. Traditional linear
feedforward and feedback approaches are discussed
and
a novel method for use of a time delay CMAC neural
network for disturbance cancellation in nonlinear
dynamical systems is presented. Appropriate
modifications to the CMAC training algorithm are
derived which allow convergent adaptation for a
variety of secondary signal paths. Analytical bounds
on the maximum learning gain are presented which
guarantee convergence of the algorithm and provide
insight into the necessary reduction in learning
gain as a function of the system parameters.
Effectiveness of the algorithm is evaluated through
mathematical analysis, simulation studies and
experimental application of the technique on an
acoustic duct laboratory model.

Contributors

Author:
Canfield, John

Further information

Biography Artist:
Dr. John Canfield received his B.S., M.S. and Ph.D. in Electrical
Engineering degrees from the University of New Hampshire. His
doctoral research was in the field of nonlinear control systems
with an emphasis on neural networks. He is currently a Design
Section Leader at Linear Technology Corporation.
Language:
English
Number of Pages:
236
Media Type:
Softcover
Publisher:
VDM Verlag Dr. Müller

Master Data

Product Type:
Paperback book
Package Dimensions:
0.22 x 0.15 x 0.014 m; 0.399 kg
GTIN:
09783639120936
DUIN:
8TNQSGME8FR
$100.99
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