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Reseach Article

Article:Modeling of an Inverted Pendulum based on Fuzzy Clustering Techniques

by E.Sivaraman, S.Arulselvi, S.P.Natarajan
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 9 - Number 4
Year of Publication: 2010
Authors: E.Sivaraman, S.Arulselvi, S.P.Natarajan
10.5120/1373-1850

E.Sivaraman, S.Arulselvi, S.P.Natarajan . Article:Modeling of an Inverted Pendulum based on Fuzzy Clustering Techniques. International Journal of Computer Applications. 9, 4 ( November 2010), 23-31. DOI=10.5120/1373-1850

@article{ 10.5120/1373-1850,
author = { E.Sivaraman, S.Arulselvi, S.P.Natarajan },
title = { Article:Modeling of an Inverted Pendulum based on Fuzzy Clustering Techniques },
journal = { International Journal of Computer Applications },
issue_date = { November 2010 },
volume = { 9 },
number = { 4 },
month = { November },
year = { 2010 },
issn = { 0975-8887 },
pages = { 23-31 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume9/number4/1373-1850/ },
doi = { 10.5120/1373-1850 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:57:46.770444+05:30
%A E.Sivaraman
%A S.Arulselvi
%A S.P.Natarajan
%T Article:Modeling of an Inverted Pendulum based on Fuzzy Clustering Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 9
%N 4
%P 23-31
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The inverted pendulum is a highly nonlinear and open loop unstable system. To develop an accurate model of the inverted pendulum, different linear and nonlinear methods of identification will be used. However one of the problems encountered during modeling is the collection of experimental data from the inverted pendulum system. Since the output data from the unstable system does not show enough information or dynamics of the system. This can be overcome by designing a feedback controller , which stabilize the system before identification can takes place. Recently Takagi-Sugeno (T-S) fuzzy modeling based on clustering techniques have shown great progress in identification of nonlinear systems. Hence in this paper, Takagi-Sugeno (T-S) model is proposed for an inverted pendulum based on fuzzy c-means , Gustafson-Kessel (G-K) and Gath-Geva (G-G) clustering techniques. Simulation results show that Gustafson-Kessel (G-K) clustering technique produces satisfactory performance.

References
Index Terms

Computer Science
Information Sciences

Keywords

Nonlinear Clustering Fuzzy Inverted Pendulum Takagi-Sugeno