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

Springer Science & Business Media
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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.

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About the author

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.

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Additional Information

Springer Science & Business Media
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Published on
Dec 28, 2005
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Computers / Computer Simulation
Computers / Desktop Applications / Design & Graphics
Science / Chemistry / Industrial & Technical
Technology & Engineering / Automation
Technology & Engineering / Electrical
Technology & Engineering / Mechanical
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The series Advances in Industrial Control aims to report and encourage of control technology transfer in control engineering. The rapid development technology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies ... , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. Nonlinear control methods continue to exert a continuing fascination for current researchers in control systems techniques. Many industrial systems are nonlinear as was so ably demonstrated in the recent Advances in Industrial Control monograph on hydraulic servo-systems by M. Jelali and A. Kroll. However, the need to use a nonlinear control technique depends on the severity of the nonlinearity and the performance specification of the application. In some cases it is imperative that a nonlinear technique be used. The type of technique which is applied usually depends on the available information on the system description. This is the key determinant in the development of new nonlinear control methods. Over the next few years it is hoped that the nonlinear control paradigm will produce several methods which will be easily and widely applicable in industrial problems. In the meantime the search and development research go on.
Transportation systems in buildings are part of everyday life: whether ferrying people twenty storeys up to the office or moving luggage to the airport check-in, 21st-century man relies on them.

Control of Traffic Systems in Buildings presents the state of the art in the analysis and control of transportation systems in buildings focusing primarily on elevator groups. The theory and design of passenger traffic and cargo transport systems are covered, together with actual operational examples and topics of special current interest such as:

• noisy, on-line and algorithmic optimization;

• simulation-based modeling of passengers and goods;

• control of cooperative agent-oriented systems;

• proposal for a benchmark to compare new control methods;

• deployment and testing of transportation systems.

Special attention is given to the techniques and uses of simulation and a working simulator is included that allows readers to explore the subject for themselves.

The safe running of such automated traffic systems, though vital, gets rather taken for granted but workers in elevator control have pioneered the development of many modern control systems for employment in all sorts of traffic and scheduled systems being among the first to realize the potential of techniques like fuzzy logic, neural networks and genetic algorithms. For this reason, this exposition of recent work in in-building transport control will be of considerable interest to researchers and engineers in many areas of control, particularly those working in optimal or supervisory control, urban transportation systems and intelligent transport systems as well as to those directly interested in the elevator control systems under discussion.

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