Modeling and identification of the bio-ethanol production process from starch: Cybernetic vs. unstructured modeling

In this work, an unstructured and a cybernetic model are proposed and compared for the Simultaneous Saccharification_- Fermentation process from Starch to Ethanol (SSFSE), in order to have good, reliable, and highly predictive models, which can be used in optimization and process control applications. The cybernetic is a novel model, which especially considers i) the starch degradation into both glucose and dextrins, and ii) the dynamic behavior of the concentration of the main enzymes involved in the intracellular processes, giving a more detailed description of the process. Furthermore, a new identification procedure based on a sensitivity index is proposed to identify the best set of parameters that not only minimizes the error function, but also contains a fewer number of parameters depending on the initial conditions of the process. Finally, an application of the two models for controlling the SSFSE process using an NMPC (following an optimal reference trajectory for the ethanol concentration) is presented, showing the potential and usefulness of each type of models.