Adaptive model of fermentation processes under uncertainty conditions

This study describes an adaptive model, which allows predicting industrial fermentation processes under uncertainty conditions. The model is based on a collection of deterministic differential thermal-controlled models. It predicts state variable dynamics under every controlling thermal profile as time series of random or fuzzy numbers, and adaptively refines parameters of their probability density or membership functions using experimental observations of the system´s state.