| Abstract: | Fermentations involving competition between two or more kinds of cells under nonideal conditions show complex profiles that are sensitive to the extra‐cellular environment. These fermentations therefore require accurate and rapid on‐line data acquisition and control. However, both on‐line measurements and modelling are difficult and expensive for large bioreactors, thus limiting the usefulness of model‐based control. While neural networks offer an alternative, they require extensive training and can be difficult to optimize for large arrays. Hybrid networks combining a few neural networks with some mathematical equations offer a good compromise. The possibility of using a hybrid model for simulation‐cum‐control has been examined here for the fed‐batch production of streptokinase. Under noideal conditions, hybrid neural models outperformed both mathematical models and arrays of neural networks, thus suggesting their viability for large‐scale fermentation monitoring and control. |
