Predictive control for industrial applications

Abstract

An overview is first provided of some of the most common formulations of Predictive Control, such as Dynamic Matrix Control (DMC), Predictive Functional Control (PFC), Preview Control and Generalized Predictive Control (GPC). The main features, advantages and disadvantages are discussed. A new algorithm, based on a so called Linear Quadratic Generalized Predictive Controller (LQGPC) is then introduced. This algorithm combines features of Predictive Control with those of Linear Quadratic Gaussian Control, providing improved stability and robustness properties. Attention then turns to the state-space formulation of the problem. An algorithm called Dynamic Performance Predictive Control is briefly outlined and some links to the Linear Quadratic Generalized Predictive Controller are exploited. Finally, applications of new Predictive Control Techniques are discussed based on industrial examples from the Power and Steel industries. These are industrial fields where Predictive Control has not yet established a leading position. However, the new algorithms, due to their improved stability and robustness properties, have the potential to provide real quality and performance benefits.