Abstract
The hybrid modelling approach for bioprocesses combines a neural network representation of the reaction rates with a mass–balance description of the reactor. A procedure for the identification of hybrid models is proposed and illustrated with an experimental case-study. The key feature is a state transformation which allows to identify separately the kinetic models of the reaction rates even if they occur simultaneously in the reactor.
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