Nonlinear control of polymerization reactor

In this work, nonlinear model based control was applied to the free radical solution polymerization of styrene in a jacketted batch reactor and its pe rformance was examined to reach the required monomer conversion and molecul ar weight. Optimal temperature profiles for the properties of polymer quali ty were evaluated using the Hamiltonian optimization method. Total simulati on program having mass and energy balances of the jacketed polymerization r eactor was used to calculate the optimal trajectories. For control purposes , several experimental and theoretical dynamic studies have been made to ob serve the validity of simulation program. Experimental and theoretical nonl inear model based control have been investigated to track the temperature a t the optimal trajectory Two types of parametric and nonparametric models w ere evaluated to achieve the temperature control. For this purpose, reactio n curve was obtained to calculate the system dynamic matrix as a nonparamet ric model. In all control work, heat input to the reactor was chosen as a m anipulated variable. Nonlinear auto regressive moving average exogenous (NA RMAX) giving a relation between heat input and reactor temperature was chos en to represent the system dynamic and this model was used to describe the related control system as a parametric model. NARMAX model parameters were determined by using Levenberg Marquard algorithm. A pseudo random binary se quence (P.R.B.S.) signal was employed to disturb the system. Total simulati on program was used to calculate the system and control parameters. Several types and orders were used to construct the NARMAX models. The efficiency and the performance of the nonlinear model based control with the NARMAX mo del and dynamic matrix were tested to calculate the best model. Nonlinear m odel based control system was used to control the reactor temperature at de sired temperature trajectory experimentally and theoretically. Theoretical simulation results were compared with experimental control data. It was con cluded that the control simulation program represents the behavior of the c ontrolled reactor temperature well. In addition. nonlinear model based cont rol keeps the reactor temperature of optimal trajectory satisfactorily. (C) 2001 Elsevier Science Ltd. All rights reserved.