An indirect adaptive control strategy for a lactic fermentation bioprocess

This paper presents the design and the analysis of an indirect adaptive control strategy for a lactic acid production that is carried out in two cascaded continuous stirred tank bioreactors. The indirect adaptive control structure is based on the nonlinear process model and is derived by combining a linearizing control law with a new parameter estimator, which plays the role of the software sensor for on-line estimation of the bioprocess unknown kinetics. The behaviour and performance of both estimation and control algorithms are illustrated by simulations applied in the case of a lactic fermentation bioprocess for which kinetic dynamics are strongly nonlinear, time-varying and completely unknown.