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Sugarcane bagasse is a cheap feedstock for one of the most significant biofuel technologies currently being developed: second-generation ethanol (E2G). Most studies regarding E2G production investigate ways to improve the efficiency of this technology. However, studies about its control are still very sparse. In this work, we tried to partially fulfill this gap, addressing the control of a multiple-effect evaporation system of a sugarcane biorefinery. A feedforward fuzzy controller was proposed with membership functions based on a dynamic phenomenological model developed in Environment for Modeling, Simulation, and Optimization (EMSO). This software was also used to carry out simulations to evaluate the disturbance rejection performance. Inference tools based on neural networks and proportional–integral (PI) controllers were also proposed as support to the Fuzzy control system. The tests showed that the Fuzzy scheme outperformed traditional proportional–integral–-derivative (PID) controllers, settling on average 66% faster with a 72% reduction of integral time absolute error (ITAE).

Application of fuzzy control in the evaporation stage of a first- and second-generation sugarcane ethanol biorefinery