Parametric identifier of metabolic networks based on robust differentiation

This study proposes a new robust parametric identifier for systems that describe the dynamical behavior of metabolic networks. This identifier implements a robust parallel differentiator that recovers the time derivative for all the metabolites involved in the metabolic network. The differentiator is based on the well-known Super-Twisting Algorithm which is applied over the variation of each metabolites that is included within the metabolic network. The derivatives are fed into a parallel nonlinear least mean square scheme that is successfuLin recovering the parameters that characterizes the metabolic network. This identifier is applied to a simplified 22-reactions metabolic network of hydrogen production in Escherichia coli using glucose as substrate. The metabolic network is simulated with parameters obtained from previous studies and they are recovered using the parametric identifier proposed in this study. All the parameter are recovered with less than 5% error.