GA optimization of OBF TS fuzzy models with linear and non linear local models

Anderson V. Medeiros*, Wagner C. Amaral, Ricardo J.G.B. Campello

*Kontaktforfatter

Publikation: Kapitel i bog/rapport/konference-proceedingKonferencebidrag i proceedingsForskningpeer review

Abstract

OBF (Orthonormal Basis Function) Fuzzy models have shown to be a promising approach to the areas of nonlinear system identification and control since they exhibit several advantages over those dynamic model topologies usually adopted in the literature. Although encouraging application results have been obtained, no automatic procedure had yet been developed to optimize the design parameters of these models. This paper elaborates on the use of a genetic algorithm (GA) especially designed for this task, in which a fitness function based on the Akaike information criterion plays a key role by considering both model accuracy and parsimony aspects. The use of linear (actually affine) and nonlinear local models is also investigated. The proposed methodology is evaluated in the modeling of a real nonlinear magnetic levitation system.

OriginalsprogEngelsk
TitelProceedings of the Ninth Brazilian Symposium on Neural Networks, SBRN'06
ForlagIEEE
Publikationsdato2006
Sider66-71
Artikelnummer4026812
ISBN (Trykt)0769526802, 9780769526805
DOI
StatusUdgivet - 2006
Udgivet eksterntJa
Begivenhed9th Brazilian Symposium on Neural Networks, SBRN'06 - Ribeirao Preto, SP, Brasilien
Varighed: 23. okt. 200627. okt. 2006

Konference

Konference9th Brazilian Symposium on Neural Networks, SBRN'06
Land/OmrådeBrasilien
ByRibeirao Preto, SP
Periode23/10/200627/10/2006
SponsorBrazilian Computer Society (SBC), Spec. Interest Group of the Int. Neural Netw. Soc. in Brazil
NavnProceedings - Brazilian Symposium on Neural Networks, SBRN
ISSN1522-4899

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