A subspace-based identification method of the Wiener model, consisting of a state-space linear dynamic block and a polynomial static nonlinearity at the output, is used to retrieve the accurate information about the nonlinear dynamics of a polymerization reactor from the input-output data. The Wiener model may be incorporated into model predictive control (MPC) schemes in a unique way that effectively removes the nonlinearity from the control problem, preserving many of the favorable properties of the linear MPC. The control performance is evaluated by simulation studies, for which the original first-principles model for a continuous methyl methacrylate polymerization reactor takes the role of the plant while the identified Wiener model is used for control purposes. On the basis of the simulation results, it is demonstrated that, under the presence of strong nonlinearities, the Wiener model predictive controller (WMPC) performed quite satisfactorily for the control of polymer qualities in a continuous polymerization reactor. The WMPC strategy proposed is validated by conducting an online digital control experiment with an online densitometer and viscometer. It is observed that the WMPC performs satisfactorily for the polymer property control of the highly nonlinear multiple-input multiple-output system with input constraints.

This paper applies the two-step method to analyze the feasibility of the desired molecular weights and develops the on-line two-step method to obtain the polymer product with the desired molecular weight distribution (MWD) under process disturbances. If adequate sensors and process model are available to predict the effects of disturbances, then midcourse correction policies are obtained by using the on-line two-step method. For an illustrative example of the on-line two-step method, we conduct the styrene solution polymerization in a batch reactor system and demonstrate the excellent performance for MWD control under the measured process disturbances.

This article presents a method to determine the trajectory of initiator concentration that will produce polymer with desired number‐ and weight‐average molecular weights at a prespecified level of monomer conversion. The optimal control theory is applied to the mathematical model for a batch methymethacrylate (MMA) solution polymerization reactor system. By imposing the constraint that initiator concentration should decrease within the range of self‐consumption by the initiation reaction, one can obtain the initiator concentration trajectory that can be tracked by feeding the initiator alone. A control scheme is constructed with a cascade proportional‐integral‐derivative (PID) control algorithm for temperature control and a micropump is installed to manipulate the initiator feed rate. The experimental results show satisfactory tracking control performance despite the nonlinear features of the polymerization reactor system. Also, the monomer conversion and the average molecular weights measured are found to be in fairly good agreement with those of model prediction, respectively. In conclusion, the polymer having desired molecular weight distribution can be produced by operating the batch reactor with the initiator supplement policy calculated from the model. © 2000 John Wiley & Sons, Inc. J Appl Polym Sci 78: 1256–1266, 2000