Fuzzy identification and predictive control of the alcoholic fermentation process
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In this work a fuzzy identification model for yeast growth applied to the specific case of alcoholic fermentation is presented. Two fuzzy techniques were applied, namely the designated Mamdani modelling and the TSK (Takagi Sugeno Kang) modelling. The results were compared with the ones obtained with a deterministic model proposed by Boulton. A predictive controller is also presented and the results obtained compared with the usual PID controller. The obtained results for the identification models and for the controller showed that both methodologies can be applied to biological processes.
