Optimal Measurement Methods for Distributed Parameter System Identification
For dynamic distributed systems modeled by partial differential equations, existing methods of sensor location in parameter estimation experiments are either limited to one-dimensional spatial domains or require large investments in software systems. With the expense of scanning and moving sensors, optimal placement presents a critical problem.
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Optimal Measurement Methods for Distributed Parameter System Identification
For dynamic distributed systems modeled by partial differential equations, existing methods of sensor location in parameter estimation experiments are either limited to one-dimensional spatial domains or require large investments in software systems. With the expense of scanning and moving sensors, optimal placement presents a critical problem.
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Optimal Measurement Methods for Distributed Parameter System Identification

Optimal Measurement Methods for Distributed Parameter System Identification

by Dariusz Ucinski
Optimal Measurement Methods for Distributed Parameter System Identification

Optimal Measurement Methods for Distributed Parameter System Identification

by Dariusz Ucinski

eBook

$86.99 

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Overview

For dynamic distributed systems modeled by partial differential equations, existing methods of sensor location in parameter estimation experiments are either limited to one-dimensional spatial domains or require large investments in software systems. With the expense of scanning and moving sensors, optimal placement presents a critical problem.

Product Details

ISBN-13: 9781135488123
Publisher: CRC Press
Publication date: 08/27/2004
Sold by: Barnes & Noble
Format: eBook
Pages: 392
File size: 9 MB

About the Author

Ucinski, Dariusz

Table of Contents

Preface, 1 Introduction, 2 Key ideas of identification and experimental design, 3 Locally optimal designs for stationary sensors, 4 Locally optimal strategies for scanning and moving observations, 5 Measurement strategies with alternative design objectives, 6 Robust designs for sensor location, 7 Towards even more challenging problems, 8 Applications from engineering, Appendices, References, Index
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