Application of nonlinear model predictive control based on different models to batch polymerization reactor

In the present work, at the previously determined optimal conditions, to control batch polymerization reactor, Linear Generalized Predictive Control (LGPC) and Nonlinear Generalized Predictive Control (NLGPC) algorithm were utilized. Several system models were applied to the control algorithms. The effect of different optimal conditions has been examined on monomer conversion, average viscosity molecular weight and chain length. At the same operating conditions of LGPC and NLGPC temperature control was used for comparison. According to the experimental results, the performance of NLGPC was obtained well than LGPC control method. In addition, the results denoted that the NLGPC control performances depend on different models and the optimum conditions.