Model Predictive Control is an important technique used in the process control industries. It has developed considerably in the last few years, because it is the most general way of posing the process control problem in the time domain. The Model Predictive Control formulation integrates optimal control, stochastic control, control of processes with dead time, multivariable control and future references. The finite control horizon makes it possible to handle constraints and non linear processes in general which are frequently found in industry. Focusing on implementation issues for Model Predictive Controllers in industry, it fills the gap between the empirical way practitioners use control algorithms and the sometimes abstractly formulated techniques developed by researchers. The text is firmly based on material from lectures given to senior undergraduate and graduate students and articles written by the authors.

This book is a printed edition of the Special Issue "New Directions on Model Predictive Control" that was published in Mathematics

Society heavily depends on infrastructure systems, such as road-traffic networks, water networks, electricity networks, etc. Infrastructure systems are hereby considered to be large-scale, networked systems, that almost everybody uses on a daily basis, and that are so vital that their incapacity or destruction would have a debilitating impact on the defense or economic security and functioning of society. The operation and control of existing infrastructures such as road-traffic networks, water networks, electricity networks, etc. are failing: too often we are confronted with capacity problems, unsafety, unreliability and inefficiency. This book concentrates on a wide range of problems concerning the way infrastructures are functioning today and discuss novel advanced, intelligent, methods and tools for the operation and control of existing and future infrastructures.