Realization of online optimizing control in semi-batch polymerizations

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This work addresses the challenge of developing and implementing online optimizing control schemes for the time-optimal operation of semi-batch polymerizations, utilizing two case studies. The first reactor is operated by Evonik Industries AG in Marl, Germany, while the second is the Chylla-Haase Reactor, a benchmark for temperature control in polymerization reactors. Various optimizing schemes of differing complexities are proposed, focusing on the simultaneous online optimization of cooling power and monomer dosage during operation. Key factors for successful industrial implementation, such as creating a reliable process model and compensating for model uncertainties, are discussed in detail. A novel method for online compensation of these uncertainties is introduced, along with a full nonlinear model predictive controller (NMPC) designed for the time-optimal operation of semi-batch polymerizations. Additionally, a simplified optimizing control scheme that tracks operation conditions close to optimality in a feedback manner is proposed and successfully implemented in an industrial setting. The effectiveness of these control schemes is demonstrated through simulations and real plant application results.