Abstract - Palanki - 9409577 A large variety of specialty chemicals are produced in batch reactors. Since batch reactors are transient in nature, the major objective is to optimize a performance index (such as yield) at the end of the batch cycle. A major problem in batch reactor operation is that changes in initial conditions and environmental conditions can cause significant batch-to-batch variations leading to significant losses in resources and time. For this reason, it is necessary to develop optimization strategies that can be implemented on-line. In this study a methodological framework for on-line optimization of batch processes with multiple inputs will be developed. The emphasis is on the experimental implementation of optimal state feedback laws in industrially important batch polymerization reactors. The copolymerization of styrene with methyl acrylate in toluene using aso-bis-iso-butyronitrile (AIBN) has been selected as a model experimental system to demonstrate the application of the on-line optimization strategy. In Phase I of the research, a mathematical model of the experimental system will be developed. In Phase II, optimal state feedback laws will be developed for end-point optimization of batch reactors with multiple inputs. The efficacy of the optimal state feedback in optimizing the performance index will be tested on the mathematical model by computer simulations. In Phase III, the on-line optimization strategy will be implemented experimentally. Several batch and semi-batch experiments will be conducted to demonstrate the ability of the optimal state feedback to calculate, on-line, the optimal operating policy when there are batch to batch variations in initial conditions and process disturbances.
