ANFIS controller for double inverted pendulum

Qiang Sheng; Zhou Qing; X. Z. Gao; Yu Shuanghe

doi:10.1109/INDIN.2008.4618147

ANFIS controller for double inverted pendulum

Qiang Sheng^*
, Zhou Qing
, X. Z. Gao
, Yu Shuanghe

^*Corresponding author for this work

School of Astronautics

Harbin Institute of Technology
Aalto University
Dalian Maritime University

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

12 Scopus citations

Abstract

A mathematical model for the double inverted pendulum is first presented. Then adaptive neural fuzzy inference system based on the state variables fusion is proposed for the control of the double inverted pendulum. The controller uses error back-propagation and least square estimator hybrid training algorithm to adjust the membership functions of each variable, optimize fuzzy rules, and identify the double inverted pendulum. Results show that proposed ANFIS controller can make the inverted pendulum stable.

Original language	English
Title of host publication	Proceedings - IEEE INDIN 2008
Subtitle of host publication	6th IEEE International Conference on Industrial Informatics
Pages	475-480
Number of pages	6
DOIs	https://doi.org/10.1109/INDIN.2008.4618147
State	Published - 2008
Event	IEEE INDIN 2008: 6th IEEE International Conference on Industrial Informatics - Daejeon, Korea, Republic of Duration: 13 Jul 2008 → 16 Jul 2008

Publication series

Name	IEEE International Conference on Industrial Informatics (INDIN)
ISSN (Print)	1935-4576

Conference

Conference	IEEE INDIN 2008: 6th IEEE International Conference on Industrial Informatics
Country/Territory	Korea, Republic of
City	Daejeon
Period	13/07/08 → 16/07/08

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10.1109/INDIN.2008.4618147

Cite this

@inproceedings{669e7f4276a44cd6bdb8d02adf440397,

title = "ANFIS controller for double inverted pendulum",

abstract = "A mathematical model for the double inverted pendulum is first presented. Then adaptive neural fuzzy inference system based on the state variables fusion is proposed for the control of the double inverted pendulum. The controller uses error back-propagation and least square estimator hybrid training algorithm to adjust the membership functions of each variable, optimize fuzzy rules, and identify the double inverted pendulum. Results show that proposed ANFIS controller can make the inverted pendulum stable.",

author = "Qiang Sheng and Zhou Qing and Gao, \{X. Z.\} and Yu Shuanghe",

year = "2008",

doi = "10.1109/INDIN.2008.4618147",

language = "英语",

isbn = "9781424421718",

series = "IEEE International Conference on Industrial Informatics (INDIN)",

pages = "475--480",

booktitle = "Proceedings - IEEE INDIN 2008",

note = "IEEE INDIN 2008: 6th IEEE International Conference on Industrial Informatics ; Conference date: 13-07-2008 Through 16-07-2008",

}

Sheng, Q, Qing, Z, Gao, XZ & Shuanghe, Y 2008, ANFIS controller for double inverted pendulum. in Proceedings - IEEE INDIN 2008: 6th IEEE International Conference on Industrial Informatics., 4618147, IEEE International Conference on Industrial Informatics (INDIN), pp. 475-480, IEEE INDIN 2008: 6th IEEE International Conference on Industrial Informatics, Daejeon, Korea, Republic of, 13/07/08. https://doi.org/10.1109/INDIN.2008.4618147

ANFIS controller for double inverted pendulum. / Sheng, Qiang; Qing, Zhou; Gao, X. Z. et al.
Proceedings - IEEE INDIN 2008: 6th IEEE International Conference on Industrial Informatics. 2008. p. 475-480 4618147 (IEEE International Conference on Industrial Informatics (INDIN)).

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

TY - GEN

T1 - ANFIS controller for double inverted pendulum

AU - Sheng, Qiang

AU - Qing, Zhou

AU - Gao, X. Z.

AU - Shuanghe, Yu

PY - 2008

Y1 - 2008

N2 - A mathematical model for the double inverted pendulum is first presented. Then adaptive neural fuzzy inference system based on the state variables fusion is proposed for the control of the double inverted pendulum. The controller uses error back-propagation and least square estimator hybrid training algorithm to adjust the membership functions of each variable, optimize fuzzy rules, and identify the double inverted pendulum. Results show that proposed ANFIS controller can make the inverted pendulum stable.

AB - A mathematical model for the double inverted pendulum is first presented. Then adaptive neural fuzzy inference system based on the state variables fusion is proposed for the control of the double inverted pendulum. The controller uses error back-propagation and least square estimator hybrid training algorithm to adjust the membership functions of each variable, optimize fuzzy rules, and identify the double inverted pendulum. Results show that proposed ANFIS controller can make the inverted pendulum stable.

UR - https://www.scopus.com/pages/publications/54849418893

U2 - 10.1109/INDIN.2008.4618147

DO - 10.1109/INDIN.2008.4618147

M3 - 会议稿件

AN - SCOPUS:54849418893

SN - 9781424421718

T3 - IEEE International Conference on Industrial Informatics (INDIN)

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EP - 480

BT - Proceedings - IEEE INDIN 2008

T2 - IEEE INDIN 2008: 6th IEEE International Conference on Industrial Informatics

Y2 - 13 July 2008 through 16 July 2008

ER -

ANFIS controller for double inverted pendulum

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