Nonlinear process-model-based control and optimization of batch polymerization reactor
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Abstract
Polymers (Ray and Laurence, 1977) have been synthesized in the laboratory for more than 150 years. When the commercial importance of polymers was realized in the early twentieth century, production began by scale-up from successful laboratory experiments. Because so little was understood about the polymerization step and the product was so difficult to characterize, a successful polymerization process was one which could reproduce the same recipe for every batch, thus producing reasonable product uniformity from batch to batch.
As might be expected, even minor modifications of the recipe produced a different product, so that a great plethora of product lines, each of small market volume, began to evolve. As the total demand for polymer products has vastly increased over the last 40 to 50 years, the method of production became more and more expensive. Thus in the last 20 years, polymer manufacturers have been working to improve the quality of their products and the efficiency of their operation through efforts: (1) to improve their ability to characterize the chemical makeup and corresponding physical properties of the various polymer products; (2) to quantitatively understand the influence of the reaction conditions on the polymer produced; and (3) where necessary, to develop more effective reactors. These efforts have required a much better understanding of polymerization kinetics and optimum recipes. The scope of this work is not to investigate a new fact about the polymerization reaction or its physical properties or aspects of reactor design, but to effectively utilize some known facts to guide the course of a polymerization processes. Therefore, our objective is to find out the best process recipes, typically feed rate (i.e., monomer, solvent, initiator) and temperature profile, and effectively maintain them during the batch time. Consequently, it requires a process control and optimization technique.