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Soft Sensors for Monitoring and Control of Industrial Processes

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  • © 2007

Overview

  • Shows the reader how to make the most of routine data gathering and storage to provide a valuable back-up and double check for hardware sensors and an alternative where these are not available
  • Integrates methods for dealing with nonlinear systems common in industrial processes
  • Real industrial case studies backed up by data sets from actual plant show readers how to adapt the methods described to their plants
  • Includes supplementary material: sn.pub/extras

Part of the book series: Advances in Industrial Control (AIC)

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Table of contents (9 chapters)

Keywords

About this book

focussed on the key steps in soft sensor design: data selection; model structure selection and model validation, respectively. Extensions to the basic steps of soft sensor design, namely soft sensor performance enhancement and the modifications needed to facilitate different industrial process applications follow in Chapter 7 and 8, respectively. Widening the applications range and role of soft sensors to fault detection and sensor validation configurations is dealt with in Chapter 9. A great strength of Soft Sensors for Monitoring and Control of Industrial Processes is the use, throughout the text, of a set of industrial case studies to demonstrate the successes and drawbacks of the different methods used to create soft sensor models. A number of different methods may be used in each separate step of the soft sensor design process and the industrial case studies are often used to provide explicit comparisons of the performance of these methods. The industrial control and process engineer will find these comparison exercises invaluable illustrations of the sort of results that might be found in industrial applications. The monograph also highlights the importance of using knowledge from industrial experts and from the existing industrial process literature. This is an important aspect of industrial control that is not very widely acknowledged or taught in control courses. Most industrial processes have already generated a significant experimental knowledge base and the control engineer should develop ways of tapping into this valuable resource when designing industrial control schemes.

Reviews

From the reviews:

"The monograph is devoted to design procedure of soft sensors and their applications for solving some industrial problems. … The monograph highlights the importance of using knowledge from industrial experts and from the existing industrial process literature. It is full of valuable information about the veracity of different methods. The monograph will be appreciated by the industrial control engineer for its practical insights and by the academic staff for its case-study applications."(Tadeusz Kaczorek, Zentralblatt MATH, Vol. 1136 (14), 2008)

Authors and Affiliations

  • Dipartimento di Ingegneria Elettrica Elettronica e dei Sistemi, Università degli Studi di Catania, Catania, Italy

    Luigi Fortuna, Salvatore Graziani

  • Dipartimento di Elettrotecnica ed Elettronica, Politecnico di Bari, Bari, Italy

    Alessandro Rizzo

  • Dipartimento di Matematica, Università degli Studi di Messina, Facoltà di Ingegneria, Messina, Italy

    Maria G. Xibilia

About the authors

Luigi Fortuna has been Professor of System Theory at the University of Catania since 1994. He has published more than 280 technical papers and is co-author of seven books including, for Springer, Soft Computing (1-85233-308-1, 2001, 280 pp, SC) and Microelectronics and Microsystems (1-85233-499-1, 2001, 222 pp, HC). He holds several USA patents. His scientific interests include automatic control, nonlinear science and complexity, chaos, cellular neural networks with applications in bioengineering. He has been an IEEE Fellow since 2000.

Salvatore Graziani received a M.S. degree in electronic engineering and a Ph.D. in electrical engineering, both from the Università degli Studi di Catania, Italy, in 1990 and 1994, respectively. In 1990 he joined the Dipartimento di Ingegneria Elettrica, Elettrica e dei Sistemi, Università di Catania, where he is an Associate Professor of Electric and Electronic Measurement and Instrumentation. His primary research interests lie in the field of sensors and actuators, signal processing, multisensor data fusion, neural networks, and smart sensors. He has co-authored several scientific papers and one book.

Maria Gabriella Xibilia holds an M.S. degree in electronic engineering and a Ph.D. in electrical engineering, both from the Università degli Studi di Catania, Italy, in 1991 and 1995, respectively. In 1998 she joined the Dipartimento di Matematica of the Università degli Studi di Messina, where she is an Assistant Professor of Automatic Control. Her primary research interests lie in the field of process control, system identification, soft computing and fault detection. She has coauthored several scientific papers and three books.

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