Filling a gap in the literature for a practical approach to the topic, this book is unique in including a whole section of case studies presenting a wide range of applications from polymerization reactors and bioreactors, to distillation column and complex fluid catalytic cracking units. A section of general tuning guidelines of MPC is also present.These thus aid readers in facilitating the implementation of MPC in process engineering and automation. At the same time many theoretical, computational and implementation aspects of model-based control are explained, with a look at both linear and nonlinear model predictive control. Each chapter presents details related to the modeling of the process as well as the implementation of different model-based control approaches, and there is also a discussion of both the dynamic behaviour and the economics of industrial processes and plants. The book is unique in the broad coverage of different model based control strategies and in the variety of applications presented. A special merit of the book is in the included library of dynamic models of several industrially relevant processes, which can be used by both the industrial and academic community to study and implement advanced control strategies.
ZoltAn K. Nagy received his PhD from Babes-Bolyai University of Cluj, where he worked as a lecturer until 2005. Before taking up his current appointment as a faculty member at Loughborough University, UK, he was NATO research fellow and visiting lecturer at the University of Illinois at Urbana-Champaign, and research associate at the University of Stuttgart, University of Heidelberg and ETH ZA1/4rich. His main research interest is in the modelbased control and optimization of chemical processes. He worked on industrial implementation of model-based control strategies with companies such as BASF and ABB, and has published over 80 papers in the field.
Arpad Imre-Lucaci received his M.S. and Ph.D. degrees in chemical engineering from Babes-Bolyai University of Cluj-Napoca in 1985 and 1999, respectively. Since 1988 he has worked in the Chemical Engineering Department of BBU Cluj-Napoca, Romania, and spent research stays at University of Stuttgart (1994) and ETH ZA1/4rich (in 2002 and 2003). His main research fields are mathematical modeling, simulation and optimization in process industries, on which he has published over 20 scientific papers.
Cristea Vasile Mircea graduated the Faculty of Electrotechnics, Romania, with specialization on process control and computer science and holds a Ph.D. degree in process control. After 8 years spent in industry he is at present Associate Professor at Babes-Bolyai University, Cluj-Napoca; his interests lie in systems theory, chemical process control, advanced process control, data acquisition and control, linear and nonlinear model based predictive control, and fuzzy control. He was director of CNCSIS Projects and has published 3 books as well as over 55 scientific papers.
Professor Paul Serban Agachi graduated in 1970 in Control Engineering at the Politehnica University of Bucharest. Obtained his Ph.D. in Chemical Engineering from the University Petroleum & Gas Ploiesti, Romania. Professional experience: design engineer, system analyst, researcher in fuel cells, process modeling, optimization and control. At present, professor of Process Control at the Department of ChemicalEngineering of Babes-Bolyai University, Cluj-Napoca and member of the Academy of Technical Sciences of Romania. He has been visiting associate at California Institute of Technology, invited professor at EAtvAs Lorand University, UNESCO Higher Education consultant. He has published 8 books and 96 scientific papers.

Filling a gap in the literature for a practical approach to the topic, this book is unique in including a whole section of case studies presenting a wide range of applications from polymerization reactors and bioreactors, to distillation column and complex fluid catalytic cracking units. A section of general tuning guidelines of MPC is also present.These thus aid readers in facilitating the implementation of MPC in process engineering and automation. At the same time many theoretical, computational and implementation aspects of model-based control are explained, with a look at both linear and nonlinear model predictive control. Each chapter presents details related to the modeling of the process as well as the implementation of different model-based control approaches, and there is also a discussion of both the dynamic behaviour and the economics of industrial processes and plants. The book is unique in the broad coverage of different model based control strategies and in the variety of applications presented. A special merit of the book is in the included library of dynamic models of several industrially relevant processes, which can be used by both the industrial and academic community to study and implement advanced control strategies.