Model predictive control of an open-loop unstable train of polymerization reactors

Abstract

Model Predictive Control (MPC) schemes have the appealing property of combining powerful multivariate control algorithms with ease of implementation and conceptual simplicity. We have applied MPC to the model of a typical non-linear process of industrial interest, involving two Continuous Stirred-Tank Reactors (CSTR) in cascade. The reaction taking place in these reactors is the polymerization of styrene in the presence of a binary initiator mixture. Under certain conditions, such a system exhibits multiple steady-states and open-loop unstable behaviour. Because of their open-loop unstable behaviour, the reactors give rise to a difficult temperature control problem. Control is achieved by manipulating the flow rates of coolant fluid circulating inside the reactors' jackets. The present work aims at designing proper control strategies for this unstable train of reactors using a Dynamic Matrix Control (DMC) algorithm and to compare such a scheme with the use of conventional digital PID controllers. The design of the DMC controller was based on a linearization of the dynamic model around an open-loop stable operating point. The implementation of the DMC algorithm was carried out using a standard formulation.