Evaluación por simulación de estrategias de control automático para fermentadores industriales de cerveza

The operation and control of beer fermentation at an industrial scale (> 3000 hL) pose significant challenges due to the dynamic nature of the process and the large reactor volumes involved. Effective control of fermentation temperature, a critical parameter, is hindered by the lack of advanced control models that consider volume heterogeneity. To address this, we implemented a compartmentalized phenomenological model to simulate the fermentation process, focusing on temperature control in the reactor. The model was utilized to compare two control strategies: a conventional Proportional-Integral-Derivative (PID) control system and a Model Predictive Control (MPC) framework, both designed to track a reference temperature profile. Simulation results highlight significant temperature variations across reactor compartments, necessitating the adoption of spatially aware control strategies. The MPC-based control system demonstrated superior performance compared to the PID approach, offering more precise tracking of the temperature reference in all compartments. These findings underscore the potential of MPC for optimizing temperature control in large-scale fermentation processes. Future work will focus on the industrial validation of the model and the control strategies for implementation in operational settings.