Constrained nonlinear predictive control for maximizing production in polymerization processes

In this brief, a new constrained nonlinear predictive control scheme is proposed for maximizing the production in polymerization processes. The key features of the proposed feedback strategy are its ability to rigorously handle the process constraints (input saturation, maximum allowed heat production, maximal temperature values, and rate of change) as well as its real time implementability due to the low dimensional control parametrization being used. Simulations are proposed to show the efficiency of the proposed feedback as well as its robustness to model uncertainties. The controller performance is also validated experimentally on a laboratory scale reactor to control the emulsion polymerization of styrene.