Model predictive control of a PVC batch reactor

This paper discusses a method to improve the quality of temperature control of the polyvinyl chloride (PVC) suspension batch reactor by implementing two Nonlinear Model Predictive Controllers (NMPCs) for this exponentially unstable process with very nonlinear behavior. The first method is based on recomputing the step response matrix at each sampling time with a double model based prediction and solving twice the optimization problem using the linear model of the process described by the step response matrix. The second method uses the rigorous model for both prediction and optimization. These methods were tested for different disturbances, and their performances were compared with those obtained with proportional-integral-derivative (PID) control. Significant improvement of temperature control was achieved using NMPC. The process model, used in both NMPC methods, is presented.