Real-time optimization in a process industry is an
application normally supported by rigorous models based on
physical-chemical equations. A new approach using neural
network and fuzzy logic technologies in real-time
applications is presented. Also featured is a methodology to
adapt a neural network and fuzzy logic process model to an
actual process condition. Results shown confirm the accuracy
that the proposed methodology can achieve. The method was
tested using actual data from a Petrobras / Regap atmospheric
and vacuum distillation unit. An online simulator based on
artificial neural network and fuzzy logic technologie
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