MIMO ADAPTIVE CONSTRAINED PREDICTIVE CONTROL CASE-STUDY - AN ENVIRONMENTAL TEST CHAMBER

In this paper, we develop a multivariable control algorithm that presents some interesting features. First, it is based on the Generalized Predictive Control approach developed by Clarke (1987). This allows one to take into account explicitly constraints on inputs, outputs, linear combinations of them and also on their derivatives or increments, this over some receding horizon. It is certainly the main feature of the algorithm. Secondly, it takes into account couplings between outputs, using a multivariable model. Thirdly, some nonlinearities are taken into account using a piecewise linear model. Lastly, changes in process model parameters are coped with, using an additional loop that consists of on-line updating of the parameters of the estimated process model using a parameter adaptation algorithm. The proposed control algorithm is experimentally evaluated on an industrial test chamber. We emphasize the influence and usefulness of the various "ingredients" involved in the proposed control algorithm.