Multivariable System Identification for Process Control by Y Zhu

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Condition
Very Good
A book that has been read but is in excellent condition. No obvious damage to the cover, with the dust jacket included for hard covers. No missing or damaged pages, no creases or tears, and no underlining/highlighting of text or writing in the margins. May be very minimal identifying marks on the inside cover. Very minimal wear and tear. See all condition definitionsopens in a new window or tab
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“Very good overall condition with light wear. Please review the photos for a visual reference.”
Pages
372
Publication Date
2001-10-08
Book Title
Multivariable System Identification for Process Control
ISBN
9780080439853
Category

About this product

Product Identifiers

Publisher
Elsevier Science & Technology
ISBN-10
0080439853
ISBN-13
9780080439853
eBay Product ID (ePID)
1978324

Product Key Features

Number of Pages
372 Pages
Language
English
Publication Name
Multivariable System Identification for Process Control
Publication Year
2001
Subject
Signals & Signal Processing, Mechanical, Manufacturing
Type
Textbook
Author
Y. Zhu
Subject Area
Technology & Engineering
Format
Hardcover

Dimensions

Item Weight
29.6 Oz
Item Length
9.5 in
Item Width
6.2 in

Additional Product Features

Intended Audience
Scholarly & Professional
LCCN
2001-036655
Dewey Edition
21
Illustrated
Yes
Dewey Decimal
670.42/7
Table Of Content
Chapter headings. Foreward. Preface. Symbols and Abbreviations. Introduction. Models of Dynamic Process and Signals. Identification Test Design and Data Pretreatment. Identification by the Least Squares Method. Extensions of the Least-Squares Method. Asymptotic method; SISO Case. Asymptotic Method; MIMO Case. Subspace Model Identification of MIMO Processes. Nonlinear Process Identification. Applications of Identification in Process Control. Model Based Fault Detection and Isolation. Refresher on Matrix Theory. Bibliography. Index.
Synopsis
Systems and control theory has experienced significant development in the past few decades. New techniques have emerged which hold enormous potential for industrial applications, and which have therefore also attracted much interest from academic researchers. However, the impact of these developments on the process industries has been limited.The purpose of Multivariable System Identification for Process Control is to bridge the gap between theory and application, and to provide industrial solutions, based on sound scientific theory, to process identification problems. The book is organized in a reader-friendly way, starting with the simplest methods, and then gradually introducing more complex techniques. Thus, the reader is offered clear physical insight without recourse to large amounts of mathematics. Each method is covered in a single chapter or section, and experimental design is explained before any identification algorithms are discussed. The many simulation examples and industrial case studies demonstrate the power and efficiency of process identification, helping to make the theory more applicable. Matlab(TM) M-files, designed to help the reader to learn identification in a computing environment, are included., Systems and control theory has experienced significant development in the past few decades. New techniques have emerged which hold enormous potential for industrial applications, and which have therefore also attracted much interest from academic researchers. However, the impact of these developments on the process industries has been limited. The purpose of Multivariable System Identification for Process Control is to bridge the gap between theory and application, and to provide industrial solutions, based on sound scientific theory, to process identification problems. The book is organized in a reader-friendly way, starting with the simplest methods, and then gradually introducing more complex techniques. Thus, the reader is offered clear physical insight without recourse to large amounts of mathematics. Each method is covered in a single chapter or section, and experimental design is explained before any identification algorithms are discussed. The many simulation examples and industrial case studies demonstrate the power and efficiency of process identification, helping to make the theory more applicable. Matlab(TM) M-files, designed to help the reader to learn identification in a computing environment, are included., Systems and control theory has experienced significant development in the past few decades. New techniques have emerged which hold enormous potential for industrial applications, and which have therefore also attracted much interest from academic researchers. However, the impact of these developments on the process industries has been limited.The purpose of Multivariable System Identification for Process Control is to bridge the gap between theory and application, and to provide industrial solutions, based on sound scientific theory, to process identification problems. The book is organized in a reader-friendly way, starting with the simplest methods, and then gradually introducing more complex techniques. Thus, the reader is offered clear physical insight without recourse to large amounts of mathematics. Each method is covered in a single chapter or section, and experimental design is explained before any identification algorithms are discussed. The many simulation examples and industrial case studies demonstrate the power and efficiency of process identification, helping to make the theory more applicable. Matlab(tm) M-files, designed to help the reader to learn identification in a computing environment, are included.
LC Classification Number
TS156.8.Z495 2001

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