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Multivariable System Identification For Process Control
 
 
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Multivariable System Identification For Process Control [Hardcover]

Y. Zhu (Author)

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Book Description

0080439853 978-0080439853 October 22, 2001 1
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 M-files, designed to help the reader to learn identification in a computing environment, are included.

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Inside This Book (learn more)
First Sentence:
System. A system is a collection of objects arranged in an ordered form to serve some purpose. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
feed water leakage, average switch time, non additive faults, combustion chamber fouling, output error method, output error model, output error criterion, asymptotic local approach, low gain direction, process settling time, feedforward variables, level control output, equation error model, innovation filter, high order model, model order selection, prediction error methods, exit thickness, residual generation, prediction error model, open loop test, prediction error criterion, faulty case, tray temperature, residual evaluation
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Model Initialization, The Page-Hinkley
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