Robustness analysis of nonlinear predictive control of fed-batch E. Coli cultures

This paper presents a nonlinear predictive control strategy for maximizing the biomass growth in fed-batch cultures of E. Coli. This objective is achieved by regulating the acetate concentration at a low measurable value, while tracking (in a compromising way) an optimal glucose feed-rate trajectory determined off-line. Robustness with respect to model uncertainties is improved by taking system/model mismatch during prediction into account. Robustness is practically assessed by means of a Monte Carlo procedure, considering statistical results obtained in the case of model parameter uncertainties.