Abstract
A first-order Takagi–Sugeno fuzzy inference engine based on the use of polynomial consequents in the fuzzy rules was applied to the identification of a thermocompression evaporator. The fuzzy system obtained proved to be suitable for the description and off-line optimization of the process based on the recirculation of sugar liquid in the equipment. Only two linguistic rules were needed to successfully describe the complicated and non-linear effects of four input variables on the outlet concentration of sugar. Supervisory control of evaporation could be realized by steering only the feed of liquid to the evaporator, or the recirculation of liquid in the evaporation section.
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