The application of economic model predictive control (EMPC) techniques in bioprocesses is scarce due to limitations in obtaining accurate dynamic models. Simplified unstructured models (e.g., Monod) can be easily developed, but their prediction capacity is poor. On the other hand, models based on dynamic flux balance analysis (dFBA) of the detailed metabolic network appear as a promising alternative. However, using dFBA inside the controller leads to a bilevel optimization problem, which could require excessive computational effort. In the present work, a control approach is proposed to tackle this limitation. By combining mass balances with a surrogate model for the metabolic network, our approach provides a significant reduction in online computation while still accurately describing the microorganism of interest. A case study of a fed-batch bioreactor of Saccharomyces cerevisiae for ethanol maximization was chosen to test the new approach. First, flux balance analysis simulations with Yeast 8.30 genome-scale model were performed, then a simple polynomial model was fitted to these data by partial least-squares regression (PLSR). The identification step showed that only 11 PLS components were necessary to allow the FBA to be replaced by the surrogate model with a good accuracy. The surrogate model was coupled to the EMPC, and the results were similar to those presented in the literature, where the bilevel optimization problem is explicitly solved. The EMPC was able to compensate for structural errors in the identification process, and it provided a higher ethanol titer in comparison to the open-loop operation. The results showed that applying surrogate models to dFBA is a viable strategy to the solution of a bilevel optimization problem.

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As the culmination of the Chemical Engineering curriculum, students face the challenging and stimulating elaboration of a whole design project that integrates all the knowledge gained throughout the course. The subject is divided into two parts, gaining a theoretical background in the ninth semester and a proposed teamwork project design with the aid of a process simulator in the tenth semester. This paper presents the challenge of designing a whiskey distillery elected by a group of students applying the project‐based learning methodology. As a strategy for a more efficient design, the process is divided into three blocks: prefermentation, fermentation, and distillation. Calculations involve mass and energy balances and the design of the different units, including the optimization of a distillation column assisted by the ASPEN HYSYS® simulator. Students must publicly present their results in front of the class and a jury formed by chemical engineers. A survey was carried out to assess the student's satisfaction and feedback. The results manifested the significance of the subject for the future and the satisfaction of the proposed teaching strategy.