Process Modelling for Control (eBook)

A Unified Framework Using Standard Black-box Techniques
eBook Download: PDF
2005 | 2005
XXXIII, 229 Seiten
Springer London (Verlag)
978-1-84628-247-8 (ISBN)

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Process Modelling for Control -  Benoit Codrons
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Process Modelling for Control concentrates on the modelling steps underlying a successful control design, answering questions like:

How should I carry out the identification of my process to obtain a good model?
How can I assess the quality of a model before to using it in control design?
How can I ensure that a controller will stabilise a real process well enough before implementation?
What is the most efficient method of order reduction to simplify the implementation of high-order controllers?

System identification, model/controller validation and order reduction are studied in a common framework. Detailed worked examples, representative of various industrial applications, are given.

This monograph uses mathematics convenient to researchers interested in real applications and to practising engineers interested in control theory. It enables control engineers to improve their methods and provides academics and graduate students with an all-round view of recent results in modelling for control.



Doctor Codrons is ideally suited to authorship in the Advances in Industrial Control Series having both academic and industrial experience. He has worked for the large French electricity supply company Électricité de France and then a four-and-a-half-year academic appointment at the Université Catholique de Louvain studying control-oriented system modelling techniques. He now works for the research arm of the Belgian national supplier as a project leader in process control.


Process Modelling for Control concentrates on the modelling steps underlying a successful control design, answering questions like:How should I carry out the identification of my process to obtain a good model?How can I assess the quality of a model before to using it in control design?How can I ensure that a controller will stabilise a real process well enough before implementation?What is the most efficient method of order reduction to simplify the implementation of high-order controllers?System identification, model/controller validation and order reduction are studied in a common framework. Detailed worked examples, representative of various industrial applications, are given.This monograph uses mathematics convenient to researchers interested in real applications and to practising engineers interested in control theory. It enables control engineers to improve their methods and provides academics and graduate students with an all-round view of recent results in modelling for control.

Doctor Codrons is ideally suited to authorship in the Advances in Industrial Control Series having both academic and industrial experience. He has worked for the large French electricity supply company Électricité de France and then a four-and-a-half-year academic appointment at the Université Catholique de Louvain studying control-oriented system modelling techniques. He now works for the research arm of the Belgian national supplier as a project leader in process control.

Introduction
Preliminary Material
Identification in Closed Loop for Better Control Design
Dealing with Controller Singularities in Closed-loop Identification
Model and Controller Validation for Robust Control in a Prediction-error Framework
Control-oriented Model Reduction and Controller Reduction
Some Final Words

Erscheint lt. Verlag 28.12.2005
Reihe/Serie Advances in Industrial Control
Zusatzinfo XXXIII, 229 p.
Verlagsort London
Sprache englisch
Themenwelt Mathematik / Informatik Informatik Theorie / Studium
Naturwissenschaften Chemie Technische Chemie
Technik Bauwesen
Technik Elektrotechnik / Energietechnik
Technik Maschinenbau
Schlagworte Bias • bopp • Control • Control Applications • control engineering • control system • Control Systems Design • Control Theory • Design • Identification • Industrial Practice • Model • Modeling • Modelling • Model Reduction • Process Control • Process Engineering • Process Modelling • Robust Control • System Identification
ISBN-10 1-84628-247-0 / 1846282470
ISBN-13 978-1-84628-247-8 / 9781846282478
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