A kriging interpolation strategy for the optimization of Acidithiobacillus ferrooxidans biomass production using fed-batch bioreactors

In this work, a procedure for the optimization of Acidithiobacillus ferrooxidans biomass production in fed-batch reactors using a model based on optimal spatial interpolation of experimental data is proposed. The approach is useful in those cases where specific growth and substrate consumption rates are unknown. Based on interpolation, the optimal values of biomass and substrate concentrations set points are obtained at the minimum of 2-dimensional cost function. In the fed-batch reactor biomass and substrate concentrations are controlled at their set points by changing the input flow and its concentration. We propose a minimum variance control strategy which improves the classical proportional plus integral control. Since the interpolation is optimal, the proposed linear control strategy allows obtaining a tight minimized upper bound of the variance error in the controlled variables.