Model predictive control is a receding horizon control policy in which a linear or quadratic
program with linear constraints is solved on-line at each sampling instance. An algorithm is …

In this tutorial, we discuss approaches to control of one or more primary variables in a
process using secondary measurements. This approach is useful when the primary variable …

This paper deals with the design of PID controllers, which have similar features to the model-
based predictive controller. A PID type control structure is defined which includes prediction …

The industrial evidence is that for many control problems, particularly those of the process
industries, the Proportional, Integral and Derivative (PID) controller is the main control tool …

Intended for control system engineers working in the chemical, refining, paper, and utility
industries, this book reviews the general characteristics of processes and control loops …

The effectiveness of proportional-integral-derivative (PID) controllers for a large class of
process systems has ensured their continued and widespread use in industry. Similarly …

An overview of the recent results on economic model predictive control (EMPC) is presented
and discussed addressing both closed-loop stability and performance for nonlinear systems …

Model predictive control is a form of control in which the current control action is obtained by
solving, at each sampling instant, a finite horizon open-loop optimal control problem, using …

The subject of this paper is to discuss selected effective known and novel structures for
advanced process control and optimization. The role and techniques of model-based …

Performance assessment of model predictive controllers is a problem of significant industrial
relevance. Model predictive controllers belong to a class of linear time‐varying controllers …