Identification of multivariable industrial processes for simulation, diagnosis and control

書誌事項

Identification of multivariable industrial processes for simulation, diagnosis and control

Yucai Zhu and Ton Backx

(Advances in industrial control)

Springer-Verlag, c1993

  • : New York
  • : Berlin

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注記

Includes bibliographical references and index

内容説明・目次

内容説明

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.

目次

  • 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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