Batch to Batch Iterative Learning Control of a Fed-Batch Fermentation Process

摘要

Batch to batch iterative learning control of a fed-batch fermentation process is studied in this paper. Taking the immediate previous batch as the reference batch, a linearised model relating the deviations in the control profiles with the deviations in the quality variable trajectories is obtained. The linearised model is used in calculating the control policy updating for the current batch through solving an optimisation problem. In order to cope with nonlinearities, the batch-wise linearised model is re-identified after each batch run. Simulation results show that the proposed method can overcome the effect of model-plant mismatches and unknown disturbance and improve the process operation from batch to batch.