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.