EXPERIMENTAL APPLICATION OF GENERALIZED PREDICTIVE CONTROL OF THE TEMPERATURE IN A POLYSTRENE POLYMERIZATION REACTOR

The performance of generalized predictive control (GPC) was examined and compared with conventional control applied to the temperature of as free radical solution polymerization of styrene in a jacketed batch reactor. Optimal conditions were obtained at different initiator concentrations by applying Lagrange's multiplier to the relevant polymerization reactor. The use of the polynomial ARIMAX model related with reactor temperature and heat input was emphasized. Model parameters were determined using the Kalman algorithm. A pseudo random binary sequence (PRBS) signal was employed in order to operate the system. The GPC control method was based on the ARIMAX model. The performance criteria of GPC in evaluating the temperature control results were the required monomer conversion and molecular weight.