Adaptive Neuro Fuzzy Inference System In Distillation Column

Abstract

Neuro-Fuzzy systems are incorporated in this thesis for learning the system under consideration.Adaptive Neuro-Fuzzy inference system (ANFIS) is one of the Neuro Fuzzy systems in which a fuzzy system is implemented in the framework of adaptive networks. ANFIS constructs an input-output mapping based both on human knowledge (in the form of fuzzy rules) and on generated input-output data pairs after certain trainings to the similar situations arising from different conditions within the system. Effective control for distillation systems in the chemical industries is considered in my work. Composition measurement is not feasible, since, these analyzers, like gas chromatographs, involve large measurement delays. As an alternative, compositions can be estimated from temperature measurements. Thus, an online estimator that utilizes temperature measurements can be used to infer the produced compositions. In this study, ANFIS estimators are designed to infer the top and bottom product compositions in a continuous distillation column and to infer the reflux drum compositions in a batch distillation column from the measurable tray temperatures. Designed estimator performances are further compared with the other types of estimators such as NN.