Semibatch Copolymerization Reactor Research Articles

Development of on-line optimization-based control strategies for a starved-feed semibatch copolymerization reactor

A real-time nonlinear optimization scheme is implemented for the high temperature starved feed semi-batch solution polymerization used to produce acrylic resins for automotive coatings. The system input and state trajectories are determined on-line to minimize a cost function defined in terms of deviation from target molecular weight and composition, and batch time. The performance of the proposed strategy is examined through numerical simulation for several study cases for semibatch butyl methacrylate and styrene (BMA/STY) free radical copolymerization. Results show that polymer quality can be assured in reduced batch time while achieving constraint satisfaction over the entire run.

Design and Application of Model-on-Demand Predictive Controller to a Semibatch Copolymerization Reactor

This article considers the design of a multivariable model-on-demand predictive controller (MoD-PC) and its application to polymer quality control in a semibatch MMA/MA copolymerization reactor. The MoD-PC is designed by combining the model-on-demand (MoD) framework with the conventional model predictive controller. For this purpose, a local autoregressive exogenous input model is constructed with a small portion of data located in the region of interest at every sample time when a model equation is needed for output prediction. This model equation is then used to calculate the optimal control input sequence. Through the open-loop test, the reaction temperature and free volume are shown to be an adequate choice for the elements of the regressor state vector in the data searching step. The validity of the identified model is corroborated by the prediction method. The results of simulation studies for the regulation and disturbance rejection problems with and without noise demonstrate that, despite the nonlinearity of the system, the MoD-PC is an effective strategy with a low computational load for the production of copolymers with desired properties.

EKF-Based model predictive control in an MMA/MA solution copolymerization reactor

An experimental study was performed to corroborate the validity of an on-line state estimator for a semibatch MMA/MA copolymerization reactor by using on-line densitometer and viscometer. A conventional extended Kalman filter(EKF) was used as the state estimator and the experiment was conducted under both isothermal and nonisothermal conditions for the purpose of application to the control of copolymer properties. Further analysis was made by using off-line measurement data for the mole fraction of MMA in the remaining monomers and the solid content. It was found that the EKF could provide a good estimate for the states of the copolymerzation system. A model predictive controller(MPC) was designed and implemented to obtain copolymers with uniform copolymer composition and the desired weight average molecular weight by adopting the feed flow rate of MM A and the reaction temperature as control inputs. The controller was proven effective with a satisfactory performance for the control of polymer properties in the semibatch copolymerization reactor.

Fuzzy control of a semi-batch copolymerization reactor

This study describes the development of a rule-based fuzzy controller for regulating the copolymer composition ( F 1) in a semi-batch solution copolymerization s. The membership functions, fuzzy ranges for errors and the controller output are defined. A fuzzy rule base has been constructed relating error to controller output based on the operator's knowledge. The performance of the fuzzy controller has been evaluated by simulating the semi-batch copolymerization reactor by means of a mathematical model. The fuzzy controller developed at one operating condition has also been tested for other operating conditions.

Synthesis of multivariable nonlinear controllers by input/output linearization

AbstractThis work concerns the synthesis of nonlinear controllers for multivariable nonlinear processes that make the closed‐loop system linear in an input/output sense. Necessary and sufficient conditions for input/output linearizability via static state feedback are derived as well as formulas for the feedback law. Once such a static state feedback is applied to the process, an external multivariable linear controller with integral action can control it to set point. The proposed control methodology is tested through simulations in a semibatch copolymerization reactor example.