Predictive Control In Process Engineering - From The Basics To The Applications

Describing the principles and applications of single-input, single output and multivariable predictive control in a simple and lively manner, this practical book discusses topics such as the handling of on-off control, non-linearities and numerical problems. It gives guidelines and methods for reducing the computational demand for real-time applications. With its many examples and several case studies (incl. injection molding machine and waste water treatment) and industrial applications (stripping column, distillation column, furnace) this is invaluable reading for students and engineers who would wish to understand and apply predictive control in a wide variety of process engineering application areas.

Prof. Robert Haber studied electrical and control engineering at the universities of Budapest and Stuttgart. He gained his doctorate from the Technical University of Budapest in 1976. Since 1988 he has been professor for process engineering at the University of Applied Science in Cologne. He is the author of more than 160 scientific papers, and a host of book chapters and books.

Dr. Ruth Bars studied electrical engineering at the University of Budapest and was awarded her PhD in 1992. Currently, she is an associate professor at the University of Technology and Economics in Budapest. She is the author of more than 100 scientific papers, and a number of book chapters and book.

Dr. Ulrich Schmitz studied chemical engineering at the University of Applied Science in Cologne, and was awarded his PhD in electrical engineering in 2007 from the Budapest University of Technology and Economics. Since 2005 he has been working at Shell's Rhineland Refinery close to Cologne in Germany. Dr. Schmitz has published more than 30 scientific papers.

Introduction to predictive control
Linear SISO model descriptions
Predictive equations of linear SISO models
Predictive on-off control
GPC of linear SISO processes
Predictive PID control algorithms
Predictive control of multivariable processes
Estimation of the prediction equations
Multi-model and multi-controller approaches
GPC of nonlinear SISO processes
Predictive Functional Control
Case studies
Industrial applications
Practical aspects and future trends