A generalized predictive controller for a wide class of industrial processes

This paper presents a formulation of generalized predictive control (GPC), easy to implement and tune, that is valid for the majority of industrial processes. The method makes use of the fact that a generalized predictive controller results in a control law that can be described with few parameters. The controller has been developed for a wide class of processes in industry and a set of simple functions relating the controller parameters to the process parameters has been obtained. With this set of functions either a fixed or a selftuning GPC can be implemented in a straightforward manner. The influence of modeling errors is analyzed, and the results obtained show the stability robustness of the method, especially with respect to uncertainties in time constant and static gain.