Parametric identifier of metabolic network associated to hydrogen production in Escherichia coli based on robust sliding-mode differentiation

Abstract

This article proposes a robust parametric identifier of systems that describe metabolic networks in microorganisms. This identifier implements a robust decentralized parallel differentiator that recovers the time variation of the concentrations of all the substances involved in the metabolic network. The sense of decentralized concept used in this study regards the application of the differentiator in each node of the network without considering the effect of the surrounding nodes. This solution can be obtained under the consideration of robustness provided by the kind of differentiator used in this study. The differentiator is based on the super-twisting algorithm (STA) which is applied to the variation of each substance that is included in the metabolic network. These derivatives are fed into a parallel nonlinear least mean square scheme that succeeds in recovering the parameters that characterize the metabolic network. This identifier is applied to a simplified metabolic network, taken from Escherichia coli that regulates hydrogen production from glucose and it is conformed by 18 reactions. The metabolic network is simulated with parameters obtained from previous studies. Then, these parameters were estimated using the parametric identifier evaluated in this study based on the STA. All the parameters were estimated with less than 5 % error.