Batch to Batch Improving Control of Yeast Fermentation

摘要

An extended framework for modeling and control of nonlinear batch processes by means of simple linear models is proposed. The framework is extended to include a batch-to-batch dynamic description of initial conditions and their effect on batch evolution. In addition, the framework is extended with measurement noise. It is shown that based on desired model properties, regularization can be applied to obtain models applicable for control from sparse and noisy data. The potential of the proposed framework is demonstrated on simulated fed-batch yeast fermentations.