A multiple models based predictive control strategy applied in polymerization reactor control

Abstract

By making use of the multiple models to predict the process outputs in future time instants, a generalized predictive controller design is developed in this paper. However, the resulting nonlinear optimization problem cannot be solved straightforwardly because the values of the weighting functions in the prediction horizon are dependent on the future values of the process outputs and inputs. To circumvent this problem, an iterative procedure is developed. The proposed design is illustrated by considering the control of a polymerization reactor, in which an isothermal free-radical polymerization of methyl methacrylate is carried out using azo-bis-isobutyronitrile as initiator and toluene as solvent. © 2003 Elsevier B.V. All rights reserved.