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

Muhammad Aziz Muslim; Goegoes Dwi Nusantoro

doi:10.1109/ISITIA.2016.7828738

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

Faculty of Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

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.

Original language	English
Title of host publication	Proceeding - 2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016
Subtitle of host publication	Recent Trends in Intelligent Computational Technologies for Sustainable Energy
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	661-664
Number of pages	4
ISBN (Electronic)	9781509017096
DOIs	https://doi.org/10.1109/ISITIA.2016.7828738
Publication status	Published - 20 Jan 2017
Event	2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016 - Lombok, Indonesia Duration: 28 Jul 2016 → 30 Jul 2016

Publication series

Name	Proceeding - 2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016: Recent Trends in Intelligent Computational Technologies for Sustainable Energy

Conference

Conference	2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016
Country/Territory	Indonesia
City	Lombok
Period	28/07/16 → 30/07/16

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

ANFIS
ARMAX
system identification
vacuum distiler

Access to Document

10.1109/ISITIA.2016.7828738

Cite this

Muslim, M. A., & Nusantoro, G. D. (2017). System identification of a vacuum distiller using ANFIS with an ARMAX structure. In Proceeding - 2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016: Recent Trends in Intelligent Computational Technologies for Sustainable Energy (pp. 661-664). Article 7828738 (Proceeding - 2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016: Recent Trends in Intelligent Computational Technologies for Sustainable Energy). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISITIA.2016.7828738

Muslim, Muhammad Aziz ; Nusantoro, Goegoes Dwi. / System identification of a vacuum distiller using ANFIS with an ARMAX structure. Proceeding - 2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016: Recent Trends in Intelligent Computational Technologies for Sustainable Energy. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 661-664 (Proceeding - 2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016: Recent Trends in Intelligent Computational Technologies for Sustainable Energy).

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title = "System identification of a vacuum distiller using ANFIS with an ARMAX structure",

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.",

keywords = "ANFIS, ARMAX, system identification, vacuum distiler",

author = "Muslim, \{Muhammad Aziz\} and Nusantoro, \{Goegoes Dwi\}",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016 ; Conference date: 28-07-2016 Through 30-07-2016",

year = "2017",

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doi = "10.1109/ISITIA.2016.7828738",

language = "English",

series = "Proceeding - 2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016: Recent Trends in Intelligent Computational Technologies for Sustainable Energy",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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booktitle = "Proceeding - 2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016",

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Muslim, MA & Nusantoro, GD 2017, System identification of a vacuum distiller using ANFIS with an ARMAX structure. in Proceeding - 2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016: Recent Trends in Intelligent Computational Technologies for Sustainable Energy., 7828738, Proceeding - 2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016: Recent Trends in Intelligent Computational Technologies for Sustainable Energy, Institute of Electrical and Electronics Engineers Inc., pp. 661-664, 2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016, Lombok, Indonesia, 28/07/16. https://doi.org/10.1109/ISITIA.2016.7828738

System identification of a vacuum distiller using ANFIS with an ARMAX structure. / Muslim, Muhammad Aziz ; Nusantoro, Goegoes Dwi.
Proceeding - 2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016: Recent Trends in Intelligent Computational Technologies for Sustainable Energy. Institute of Electrical and Electronics Engineers Inc., 2017. p. 661-664 7828738 (Proceeding - 2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016: Recent Trends in Intelligent Computational Technologies for Sustainable Energy).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - System identification of a vacuum distiller using ANFIS with an ARMAX structure

AU - Muslim, Muhammad Aziz

AU - Nusantoro, Goegoes Dwi

PY - 2017/1/20

Y1 - 2017/1/20

N2 - 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.

AB - 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.

KW - ANFIS

KW - ARMAX

KW - system identification

KW - vacuum distiler

UR - https://www.scopus.com/pages/publications/85016784832

U2 - 10.1109/ISITIA.2016.7828738

DO - 10.1109/ISITIA.2016.7828738

M3 - Conference contribution

AN - SCOPUS:85016784832

T3 - Proceeding - 2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016: Recent Trends in Intelligent Computational Technologies for Sustainable Energy

SP - 661

EP - 664

BT - Proceeding - 2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016

Y2 - 28 July 2016 through 30 July 2016

ER -

Muslim MA , Nusantoro GD. System identification of a vacuum distiller using ANFIS with an ARMAX structure. In Proceeding - 2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016: Recent Trends in Intelligent Computational Technologies for Sustainable Energy. Institute of Electrical and Electronics Engineers Inc. 2017. p. 661-664. 7828738. (Proceeding - 2016 International Seminar on Intelligent Technology and Its Application, ISITIA 2016: Recent Trends in Intelligent Computational Technologies for Sustainable Energy). doi: 10.1109/ISITIA.2016.7828738

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

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UN SDGs

Keywords

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