Optimal control of molecular weight and particle size distributions in a batch suspension polymerization reactor

摘要

Mechanistic modelling is an engineering approach to simulate reasonable physical and chemical processes to develop a model to describe the behaviour of a system. Mathematical models are commonly adopted to explore the physical limits of a process, and are applied to process development, optimization and control. In this work, the population balance model and the moment technique have been utilized to model a suspension polymerization reactor and predict the dynamic evolution of particle size and molecular weight distributions. These distributions are two important factors that affect the physical, rheological and mechanical properties of a polymer, and its final product quality. The cell average technique has been applied to solve the population balance equation, and demonstrate the model predictive capability by comparing its predictions with those obtained from experimental data published in the literature. In addition, the effects of initiator, chain transfer agent, stabilizer concentrations, temperature, and agitation rate on the final particle size and molecular weight distributions have been investigated. An optimal control strategy has been used to obtain the desired molecular weight distribution by manipulating the initiator concentration, concentration of the chain transfer agent and its addition time, and controlling the reactor temperature. Also, the impeller speed and initial value of the stabilizer have been utilized to achieve the desired final particle size distribution. The simulation results indicate that the control objectives have been achieved, and show that the proposed controllers are robust to a mismatched model.