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Process Modelling for Control : A Unified Framework Using Standard Black-Box Techniques

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Title: Process Modelling for Control : A Unified Framework Using Standard Black-Box Techniques
Author: Benoit Codrons
ISBN: 1852339187 / 9781852339180
Format: Hard Cover
Pages: 229
Publisher: Springer Verlag
Year: 2005
Availability: In Stock
     
 
  • Description
  • Contents

Many process control books focus on control design techniques, taking the construction of a process model for granted. Process Modelling for Control concentrates on the modelling steps underlying a successful design, answering questions like:

How should I carry out the identification of my process in order to obtain a good model?

How can I assess the quality of a model with a view to using it in control design?

How can I ensure that a controller will stabilise a real process sufficiently well before implementation?

What is the most efficient method of order reduction to facilitate the implementation of high-order controllers?

Different tools, namely system identification, model/controller validation and order reduction are studied in a framework with a common basis: closed-loop identification with a controller that is close to optimal will deliver models with bias and variance errors ideally tuned for control design. As a result, rules are derived, applying to all the methods, that provide the practitioner with a clear way forward despite the apparently unconnected nature of the modelling tools. Detailed worked examples, representative of various industrial applications, are given: control of a mechanically flexible structure; a chemical process; and a nuclear power plant.

Process Modelling for Control uses mathematics of an intermediate level convenient to researchers with an interest in real applications and to practising control engineers interested in control theory. It will enable working control engineers to improve their methods and will provide academics and graduate students with an all-round view of recent results in modelling for control.

Preface
List of Figures
List of Tables
Symbols and Abbreviations

Chapter 1 : Introduction
Chapter 2 : Preliminary Material
Chapter 3 : Identification in Closed Loop for Better Control Design
Chapter 4 : Dealing with Controller Singularities in Closed-Loop Identification
Chapter 5 : Model and Controller Validation for Robust Control in a Prediction-Error Framework
Chapter 6 : Control-Oriented Model Reduction and Controller Reduction
Chapter 7 : Some Final Words

References
Index

 
 
 
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