Online estimation using dynamic flux balance model and multiparametric programming

An approach is proposed for online estimation of bounds on metabolite's concentrations based on limited measurements and Dynamic Flux Balance Models (DFBM) which use linear programming (LP) to model the evolution of metabolites with time. A Weighted primal-dual method to address the multiplicity of solutions of DFBMs is combined with multiparametric nonlinear programming (mpNLP) for set membership estimation. The set membership estimation (SME) approach is used to propagate the uncertainty onto metabolites' concentrations over time. By only measuring biomass concentration and culture volume, bounds of metabolites' concentrations can be estimated online by SME during the fermentation. The proposed algorithm is applied to batch and fed-batch fermentation of E. coli. (C) 2022 Elsevier Ltd. All rights reserved.