Automatic fuzzy membership function tuning using the particle swarm optimisation

Fang, G; Kwok, NM; Ha, Q

Automatic fuzzy membership function tuning using the particle swarm optimisation

Fang, G Kwok, NM Ha, Q

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008, 2008, 2 pp. 324 - 328
Issue Date:: 2008-12-01

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Field	Value	Language
dc.contributor.author	Fang, G	en_US
dc.contributor.author	Kwok, NM	en_US
dc.contributor.author	Ha, Q https://orcid.org/0000-0003-0978-1758	en_US
dc.date.issued	2008-12-01	en_US
dc.identifier.citation	Proceedings - 2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008, 2008, 2 pp. 324 - 328	en_US
dc.identifier.isbn	9780769534909	en_US
dc.identifier.uri	http://hdl.handle.net/10453/11065
dc.description.abstract	Fuzzy logic controllers (FLCs) are developed to exploit human expert knowledge in designing control systems. While the fuzzy rules are relatively easy to obtain, fuzzy membership function (MF) tuning could be a time consuming exercise. In this paper the particle swarm optimization technique is employed to automatically tune the MFs of a Mamdani-type of fuzzy controller. The effectiveness of the proposed controller is demonstrated by the control performance of such an FLC of a nonlinear water tank system. The results are compared favourably to a PSO tuned PID controller. © 2008 IEEE.	en_US
dc.relation.ispartof	Proceedings - 2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008	en_US
dc.relation.isbasedon	10.1109/PACIIA.2008.105	en_US
dc.title	Automatic fuzzy membership function tuning using the particle swarm optimisation	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2	en_US
utslib.for	0915 Interdisciplinary Engineering	en_US
dc.location.activity	Wuhan China	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CBI - Centre for Built Infrastructure
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	2	en_US

Abstract:

Fuzzy logic controllers (FLCs) are developed to exploit human expert knowledge in designing control systems. While the fuzzy rules are relatively easy to obtain, fuzzy membership function (MF) tuning could be a time consuming exercise. In this paper the particle swarm optimization technique is employed to automatically tune the MFs of a Mamdani-type of fuzzy controller. The effectiveness of the proposed controller is demonstrated by the control performance of such an FLC of a nonlinear water tank system. The results are compared favourably to a PSO tuned PID controller. © 2008 IEEE.

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http://hdl.handle.net/10453/11065