TABLE OF CONTENTS Leading industry has always required tools for increasing production rate and/or product quality while keeping the costs as low as possible. Doubtless, one of these tools is automatic process control.
In the early days, the control engineer essentially used their knowledge of the process and their understanding of the underlying physics to design very simple controllers, such as PID controllers. Analysis methods were combined with an empirical approach of the problem to design controllers with an acceptable level of performance.
During the last decades, with the increasing competition on the markets, more powerful control techniques have been developed and used in various industrial sectors in order to increase their productivity. A typical example is that of Model-based Predictive Control (MPC) in the petrochemy, where improving the pureness of some products by a few percent can yield very important profits. An interesting aspect of MPC is that it was born more than 30 years ago and developed in the industrial world, based on a very pragmatic approach of what optimal multivariable industrial control could be. It only began to arouse the interest of the scientific community much later.
More recently, advances in numerical computation and in digital electronics have allowed process control to permeate everybody's life: it is present in your kitchen, in your car, in your CD player, etc.
Industrial sectors that have until now been very traditional in their approach of process control, like the electricity...
