Non-linear predictive control of an extractive alcoholic fermentation process

Abstract In this work a SISO non-linear predictive controller was developed for an extractive alcoholic fermentation process. The internal model of the controller was represented by a functional link network (FLN). This model was identified using simulated data generated from a deterministic mathematical model whose kinetic parameters were determined experimentally. The FLN structure presented good non-linear approximation ability, with the advantage that the estimation of its weights is a linear optimization problem. The results show that the proposed algorithm has a great potential to identification and control of non-linear processes.

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