Uniformly Bounded Error Estimator for Bioprocess with Unstructured Cell Growth Models

In this paper, we proposed a uniformly bounded error estimator for a common class of bioreactor models. The biomass and other products are estimated by means of substrate concentration measurements employing the characteristics of the unstructured cell growth models, which are linearly dependent. The estimation methodology is based on a suitable change of variable which allows generating artificial variables to infer the remaining mass concentrations constructing a differential-algebraic structure. The proposed methodology is applied to a class of Monod unstructured kinetic model with success. Some remarks about the convergence characteristics of the proposed estimator are given and numerical simulations show its satisfactory performance.