Control of a solution copolymerization reactor using piecewise linear models

This paper presents an implementation of a model predictive control (MPC) algorithm using piecewise linear models on an industrial case study: Solution copolymerization of methylmethacrylate and vinyl acetate. The control algorithm is a receding horizon scheme with a quasi-infinite horizon objective function which has finite and infinite horizon cost components. The finite horizon cost consists of free input variables that direct the system towards a terminal region which contains the desired operating point. The infinite horizon cost has an upper bound and takes the system to the final operating point. The nonlinear system is represented with multiple linear models obtained by Jacobian linearization at points that are chosen along a transient trajectory between two operating points. The control approach was successfully implemented during a transition from one operating point to another. Significant improvement was observed in reducing the transition period, hence the amount of off-specification product produced during the transition period, as the number of linear models was increased to represent the nonlinear system. Furthermore, the proposed approach is extended to incorporate output feedback.