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Multi-Resolution Methods for Modeling and Control of Dynamical Systems

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Synopses & Reviews

Publisher Comments:

Unifying the most important methodology in this field, Multi-Resolution Methods for Modeling and Control of Dynamical Systems explores existing approximation methods as well as develops new ones for the approximate solution of large-scale dynamical system problems. It brings together a wide set of material from classical orthogonal function approximation, neural network input-output approximation, finite element methods for distributed parameter systems, and various approximation methods employed in adaptive control and learning theory.

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With sufficient rigor and generality, the book promotes a qualitative understanding of the development of key ideas. It facilitates a deep appreciation of the important nuances and restrictions implicit in the algorithms that affect the validity of the results produced. The text features benchmark problems throughout to offer insights and illustrate some of the computational implications. The authors provide a framework for understanding the advantages, drawbacks, and application areas of existing and new algorithms for input-output approximation. They also present novel adaptive learning algorithms that can be adjusted in real time to the various parameters of unknown mathematical models.

Book News Annotation:

This book examines existing approximation methods and explores methods for developing new methods for the approximate solution of large-scale dynamical system problems. It offers a framework for understanding the advantages, drawbacks, and application areas of algorithms for input- output approximation. It also presents novel adaptive learning algorithms that can be adjusted in real time to the various parameters of unknown mathematical models. The book brings together ideas from classical orthogonal function approximation, neural network input-output approximation, finite element methods for distributed parameter systems, and various approximation methods employed in adaptive control and learning theory. Computational implications are illustrated with benchmark problems. An appendix of color charts is included. Annotation ©2008 Book News, Inc., Portland, OR (booknews.com)

Synopsis:

Multi-Resolution Methods for Modeling and Control of Dynamical Systems discusses the underlying principles of input/output data approximation and issues associated with modeling large-scale dynamical systems. A number of techniques are applied that cover classical finite element methods, adaptive control, and neural networks to solve various problems in engineering disciplines. The book presents these diverse topics in an integrated manner derived from dynamical systems, estimation, optimization, and approximation theory. It also provides MATLAB(R) code throughout.

Product Details

ISBN:
9781584887690
Author:
Junkins, John L.
Publisher:
Chapman & Hall/CRC
Author:
Singla, Puneet
Subject:
Mechanics - General
Subject:
Mathematical models
Subject:
Systems engineering
Subject:
Engineering - General
Subject:
Systems engineering -- Mathematical models.
Subject:
Physics-Classical Mechanics
Series:
Chapman & Hall/CRC Applied Mathematics and Nonlinear Science
Publication Date:
20080831
Binding:
Hardcover
Language:
English
Illustrations:
Y
Pages:
299
Dimensions:
9.30x6.20x.80 in. 1.27 lbs.

Related Subjects

Engineering » Engineering » General Engineering
Science and Mathematics » Mathematics » General
Science and Mathematics » Physics » Classical Mechanics

Multi-Resolution Methods for Modeling and Control of Dynamical Systems New Hardcover
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Product details 299 pages Chapman & Hall/CRC - English 9781584887690 Reviews:
"Synopsis" by , Multi-Resolution Methods for Modeling and Control of Dynamical Systems discusses the underlying principles of input/output data approximation and issues associated with modeling large-scale dynamical systems. A number of techniques are applied that cover classical finite element methods, adaptive control, and neural networks to solve various problems in engineering disciplines. The book presents these diverse topics in an integrated manner derived from dynamical systems, estimation, optimization, and approximation theory. It also provides MATLAB(R) code throughout.
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