System identification of a vacuum distiller using ANFIS with an ARMAX structure

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Muhammad Aziz Muslim, Goegoes Dwi Nusantoro

2017 Proceeding - 2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016: Recent Trends in Intelligent Computational Technologies for Sustainable Energy Conference paper Cited by 1 Quartile

Abstract

As model complexity increased and unknown disturbance introduced, system identification became a useful method to solve necessity of the system model. This paper proposed an auto regressive moving average with exogenous input (ARMAX) structure system identification using Adaptive Neuro-fuzzy Inference System (ANFIS) for a Vacuum distiller. This vacuum distiller is used for bioethanol production. This approach differs from the conventional through the introduction of vacuum pressure disturbance as an exogenous input. Experimental results show that proposed method has comparable performance to the conventional Extended Least Square method. © 2016 IEEE.

Affiliations

Electrical Engineering Department, Brawijaya University, Malang, Indonesia