(574j) Dynamic Optimization of Mma and Vac Copolymerization Process

Increasing worldwide market competitiveness and reduced profit margins are pressing chemical and process industries to move towards a predictive control approach, based on first-principles mathematical models, as well as plant dynamic optimization.

In this perspective, the paper focuses on the development of a nonlinear model predictive control (NMPC) to manage the copolymerization process of methyl methacrylate (MMA) and vinyl acetate (VAc), consisting of a jacketed continuous stirred tank reactor, a separator, and a recycle loop. This system presents a highly complex behavior, thus making difficult the success the controllers based on linear models.

A detailed differential and algebraic mathematical model as well as process operating conditions were obtained from the literature (Congalidis et al., 1989). Also, improvements in kinetic parameters proposed by Maner and Doyle (1997) have been considered. The mathematical model, which consists of 53 differential and algebraic equations, is implemented in Fortran 90/95, to simulate the plant and setup the NMPC, which is fundamental for those systems characterized by long process transients and strong nonlinear dynamics, such as polymerization plants. The numerical solution is performed by using IMSL library.

Keywords: Nonlinear Model Predictive Control; dynamic optimization problems; copolymerization.