Multivariable System Identification For Process Control (Enhanced Edition) Multivariable System Identification For Process Control (Enhanced Edition)

Multivariable System Identification For Process Control (Enhanced Edition‪)‬

    • $299.99
    • $299.99

Publisher Description

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.

RELEASED
2001
October 8
LANGUAGE
EN
English
LENGTH
372
Pages
PUBLISHER
Elsevier Science
SELLER
Elsevier Ltd.
SIZE
12.8
MB

More Books Like This

Nonlinear Regression Modeling for Engineering Applications Nonlinear Regression Modeling for Engineering Applications
2016
Frontiers in Statistical Quality Control 10 Frontiers in Statistical Quality Control 10
2012
Design and Analysis of Simulation Experiments Design and Analysis of Simulation Experiments
2015
Numerical Methods for Reliability and Safety Assessment Numerical Methods for Reliability and Safety Assessment
2014
Inductive Learning Algorithms for Complex Systems Modeling Inductive Learning Algorithms for Complex Systems Modeling
2019
Chemometrics Chemometrics
2016