文摘
Real-time optimization-based control methodologies in emulsion (co)polymerization allow achievement of a significant intensification of the process and increase of the product quality. This paper describes the development of the fast and computationally simple process model of continuous styrene and n-butyl acrylate emulsion copolymerization for use in nonlinear model predictive control (NMPC) of a smart-scale tubular reactor. The model predictions agree well with experimental data for monomer conversion, copolymer composition, temperature profile, average particle size, and number-average molecular weight. To account for the slower reaction rate at the beginning of the reaction, the model incorporates a thermodynamic description of comonomer partitioning between particle, water, and droplet phases based on Morton equations. For the purpose of the process model, a simple empirical function representing the solution of Morton partitioning was implemented. The number concentration of particles was estimated from measured monomer conversion profiles, as the predictions by first-principle nucleation models generally provide values substantially different from experiments. After the model incorporation into a framework for online state estimation and control, it will be used for open- and closed-loop control of the smart-scale tubular reactor.