For the on-line monitoring of the parameters and states of aerobic fermentation batch processes three parallel software sensors for biomass concentration monitoring were developed, which use mutually independent measured input signals: the oxygen uptake rate, the carbon dioxide excretion rate and the reaction heat flow. The software sensors are based on a linear model, where the parameters of the model are estimated using the recursive least squares method. The model was upgraded with a mechanism for a time-varying forgetting factor to enable good tracking of the estimated parameters during rapid and large changes in the non-linear and, in certain phases of the production, very dynamic process. The estimates given by all three software sensors are in good agreement with the measurements acquired off-line. The developed software sensors make it possible to achieve accurate process identification, mutual control of individual sensors and fault detection in the process. In this way, better supervision and more accurate monitoring of the industrial fermentation process is possible, where reliability of the operation is of key importance.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.