Identification of Multivariable Industrial Processes: for Simulation, Diagnosis and Control

✍ Scribed by Yucai Zhu PhD, Ton Backx PhD (auth.)

• Publisher: Springer-Verlag London
• Year: 1993
• Tongue: English
• Leaves: 199
• Series: Advances in Industrial Control
• Edition: 1
• Category: Library

✦ Synopsis

Identification of Multivariable Industrial Processes presents a unified approach to multivariable industrial process identification. It concentrates on industrial processes with reference to model applications. The areas covered are experiment design, model structure selection, parameter estimation as well as error bounds of the transfer function. This publication is intended to fill the gap between modern systems and control theory and industrial application. It is based on the results of 10 years of research and application experiences. The theories and models discussed are fully explained and illustrated with case studies. At an early stage the reader is introduced to real applications.

✦ Table of Contents

Front Matter....Pages i-xiii
Introduction....Pages 1-7
Linear Models of Dynamic Processes and Signals....Pages 8-20
Identification Experiments and Data Pre-Treatment....Pages 21-36
Identification by the Least-Squares Method....Pages 37-67
Extensions of the Least-Squares Method....Pages 68-96
MIMO Process Identification: A Markov Parameter Approach....Pages 97-107
Identification for Robust Control; SISO Case....Pages 108-135
Identification for Robust Control; MIMO Case....Pages 136-158
Identification and Robust Control of the Glass Tube Process....Pages 159-166
Identification for Fault Diagnosis; Estimation of Continuous-Time Models....Pages 167-175
Back Matter....Pages 176-187

✦ Subjects

Control; Manufacturing, Machines, Tools; Computer Hardware; Software Engineering/Programming and Operating Systems; Organization/Planning