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Describing the principles and applications in a simple and lively manner, this practical book considers such issues as the handling of discontinuous control valves, non-linearities and numerical problems. With its many examples and several industrial case studies, including the injection molding machine, waste water treatment and steam consumption in a stripping column, this is invaluable reading for a wide variety of application areas, such as chemicals, food processing, automotive, aerospace, metallurgy or pulp and paper.
Robert Haber had studied electrical engineering at the Budapest University of Technology, where he also has received the Ph.D. in control theory. He is currently head of the Laboratory for Process Automation in the Faculty of Process Engineering, Energy and Mechanical Systems at the Cologne University of Applied Sciences. His research interests include process automation, experimental identification, model based control and intelligent process data analysis.
Ruth Bars graduated at the Electrical Engineering Faculty of the Budapest University of Technology, Hungary, where she has gained also her Ph.D. degree. Currently she is associate professor at the Department of Automation and Applied Informatics at the Budapest University of Technology and Economics. Her research interests are in predictive control and in developing new ways of control education. He was involved in IFAC International Federation of Automatic Control as Technical and Coordinating Committee chair.
Ulrich Schmitz studied chemical engineering and plant design at the Cologne University of Applied Sciences. Prior to this he was working as an operator in a petrochemical plant. From 2001 till 2005 he was a scientific assistant at the Cologne University of Applied Sciences and took part in a cooperative doctoral project between the Universities in Cologne and Budapest. In 2007 he received his Ph.D. from the Budapest University of Technology and Economics. Since 2005 he has been working as an APC technologist for Shell Deutschland Oil at the Rhineland Refinery in Germany.
Table of Contents
Predictive Control: Basics Linear SISO (Single-Input, Single-Output) Model Descriptions Predictive on-off Control Prediction of linear SISO Processes Dynamic Matrix Control (DMC) Generalized Predictive Control (GPC) of linear SISO Processes Predictive PI(D) Control Algorithms GPC of linear MIMO (Multi-Input, Multi-Output) Processes Estimation of the Prediction Equations GPC of nonlinear SISO Processes Using an Industrial Program Package for Predictive Control Case Studies and Applications Methodology and Experiences