Identification of multivariable industrial processes for simulation, diagnosis and control
Author(s)
Bibliographic Information
Identification of multivariable industrial processes for simulation, diagnosis and control
（Advances in industrial control）
Springer-Verlag, c1993
- : New York
- : Berlin
Available at / 15 libraries
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Hokkaido University, Faculty and Graduate School of Engineering図書
: BerlinDC20:670.42/Z613570387307
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Note
Includes bibliographical references and index
Description and Table of Contents
Description
This monograph 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 and 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
- Linear Models of Dynamic Processes and Signals.-Identification Experiment and Data Pre-Treatment.-Identification by the Least Squares Method.- Extensions of the Least-Squares Method.- MIMO Process Identification: A Markov Parameter Approach.- Identification for Robust Control
- SISO Case.- Identification for Robust Control
- MIMO Case.-Identification and Robust Control of the Glass Tube Process.-Identification for Fault Diagnosis
- Estimation of Continuous-Time Models.
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