Identification of Multivariable Industrial Processes
Subtitle: for Simulation, Diagnosis and Control
By: by Yucai Zhu, Ton Backx
Contributors: Backx, Ton
Series: Advances in Industrial Control; Advances in industrial control
Publisher: Springer London
Published: 1993
Place of publication: London
Language: eng
Format: [electronic resource] :
Number of pages: 187
ISBN-13: 9781447120605; 9781447120582
Subjects: Computer hardware; Engineering; Business planning; Machinery; Software engineering
Description: 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.
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Table of contents: title: Contents: Introduction; title: Linear Models of Dynamic Processes and Signals; title: Identification Experiments and Data Pre-Treatment; title: Identification by the Least-Squares Method; title: Extensions of the Least-Squares Method; title: MIMO Process Identification: A Markov Parameter Approach; title: Identification for Robust Control; SISO Case; title: Identification for Robust Control; MIMO Case; title: Identification and Robust Control of the Glass Tube Process; title: Identification for Fault Diagnosis; Estimation of Continuous-Time Models.