Dr. Liu received the BS and MS degrees in Control Science and Engineering from Zhejiang University in 2003 and 2006, respectively. He received the PhD degree in Chemical Engineering from the University of California, Los Angeles in 2011. Before joining the University of Alberta in April, 2012, Dr. Liu was a postdoctoral researcher at the University of California, Los Angeles. His research interests are in the general areas of process control theory and practice with emphasis on model predictive control, networked and distributed control, process monitoring, and real-time control of chemical processes and energy generation systems.Professor Panagiotis Christofides obtained his PhD from the University of Minnesota in 1996 and he has been a professor at the University of California, Los Angeles since 2004. He is a fellow of various professional societies:  the American Association for the Advancement of Science, the International Federation of Automatic Control and the IEEE.He is the author of numerous research papers, as well as two previous books published by Springer and has much experience of conference organization having served on various boards at various times, among them as the AIChE Director on the American Automatic Control Council.

“The reviewed book deals with stability and performance analysis of nonlinear control systems under economic model predictive control (EMPC). … the book builds a bridge between the theory and practice and provides an excellent balance between theoretical results and their application-specific implementation.” (Petro Feketa, zbMATH 1405.93004, 2019)“This book presents a comprehensive introduction to the topic of economic model predictive control (EMPC). … Every chapter contains illustrations of the presented results though applications to chemical process control.” (Dante Kalise, Mathematical Reviews, February, 2019)

• Introduction.- Background on Nonlinear Systems, Control, and Optimization.- Brief Overview of EMPC Methods and some Preliminary Results.- Lyapunov-Based EMPC.- State Estimation and EMPC.- Two-Layer EMPC Systems.- EMPC Systems: Computational Efficiency and Real-Time Implementation.

Dr. Liu received the BS and MS degrees in Control Science and Engineering from Zhejiang University in 2003 and 2006, respectively. He received the PhD degree in Chemical Engineering from the University of California, Los Angeles in 2011. Before joining the University of Alberta in April, 2012, Dr. Liu was a postdoctoral researcher at the University of California, Los Angeles. His research interests are in the general areas of process control theory and practice with emphasis on model predictive control, networked and distributed control, process monitoring, and real-time control of chemical processes and energy generation systems.Professor Panagiotis Christofides obtained his PhD from the University of Minnesota in 1996 and he has been a professor at the University of California, Los Angeles since 2004. He is a fellow of various professional societies:  the American Association for the Advancement of Science, the International Federation of Automatic Control and the IEEE.He is the author of numerous research papers, as well as two previous books published by Springer and has much experience of conference organization having served on various boards at various times, among them as the AIChE Director on the American Automatic Control Council.

“The reviewed book deals with stability and performance analysis of nonlinear control systems under economic model predictive control (EMPC). … the book builds a bridge between the theory and practice and provides an excellent balance between theoretical results and their application-specific implementation.” (Petro Feketa, zbMATH 1405.93004, 2019)“This book presents a comprehensive introduction to the topic of economic model predictive control (EMPC). … Every chapter contains illustrations of the presented results though applications to chemical process control.” (Dante Kalise, Mathematical Reviews, February, 2019)

• Introduction.- Background on Nonlinear Systems, Control, and Optimization.- Brief Overview of EMPC Methods and some Preliminary Results.- Lyapunov-Based EMPC.- State Estimation and EMPC.- Two-Layer EMPC Systems.- EMPC Systems: Computational Efficiency and Real-Time Implementation.

Dr. Liu received the BS and MS degrees in Control Science and Engineering from Zhejiang University in 2003 and 2006, respectively. He received the PhD degree in Chemical Engineering from the University of California, Los Angeles in 2011. Before joining the University of Alberta in April, 2012, Dr. Liu was a postdoctoral researcher at the University of California, Los Angeles. His research interests are in the general areas of process control theory and practice with emphasis on model predictive control, networked and distributed control, process monitoring, and real-time control of chemical processes and energy generation systems.Professor Panagiotis Christofides obtained his PhD from the University of Minnesota in 1996 and he has been a professor at the University of California, Los Angeles since 2004. He is a fellow of various professional societies:  the American Association for the Advancement of Science, the International Federation of Automatic Control and the IEEE.He is the author of numerous research papers, as well as two previous books published by Springer and has much experience of conference organization having served on various boards at various times, among them as the AIChE Director on the American Automatic Control Council.

“The reviewed book deals with stability and performance analysis of nonlinear control systems under economic model predictive control (EMPC). … the book builds a bridge between the theory and practice and provides an excellent balance between theoretical results and their application-specific implementation.” (Petro Feketa, zbMATH 1405.93004, 2019)“This book presents a comprehensive introduction to the topic of economic model predictive control (EMPC). … Every chapter contains illustrations of the presented results though applications to chemical process control.” (Dante Kalise, Mathematical Reviews, February, 2019)

• Introduction.- Background on Nonlinear Systems, Control, and Optimization.- Brief Overview of EMPC Methods and some Preliminary Results.- Lyapunov-Based EMPC.- State Estimation and EMPC.- Two-Layer EMPC Systems.- EMPC Systems: Computational Efficiency and Real-Time Implementation.