Multicriteria dynamic optimization of an emulsion copolymerization reactor

Abstract

Abstract A multicriteria optimization approach based on an evolutionary algorithm has been developed to determine the optimal control policy for a fed-batch emulsion copolymerization reactor, particularly for styrene and butyl acrylate in the presence of n-C12 mercaptan as chain transfer agent. The process model was elaborated and validated experimentally in order to predict the global monomer conversion, the number and weight average molecular weights, the particle size distribution and the residual monomers mass fraction. The process objectives were to produce core–shell particles (hard core and smooth shell) with specific end-use properties and high productivity. This has been achieved by the maximization of the monomers overall conversion at the end of the process and the minimization of the error between the glass transition temperature and a designed profile subject to a set of operational constraints. The nondominated Pareto solutions obtained were ranked according to a decision making aid method based on a decision maker preferences and experience using multi-attribute utility theory. Finally, the best solution was implemented experimentally.