Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/61710
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dc.titleA self-organizing fuzzified basis function network control system applicable to nonlinear servomechanisms
dc.contributor.authorLee, T.H.
dc.contributor.authorNie, J.H.
dc.contributor.authorTan, W.K.
dc.date.accessioned2014-06-17T06:43:07Z
dc.date.available2014-06-17T06:43:07Z
dc.date.issued1995-09
dc.identifier.citationLee, T.H.,Nie, J.H.,Tan, W.K. (1995-09). A self-organizing fuzzified basis function network control system applicable to nonlinear servomechanisms. Mechatronics 5 (6) : 695-713. ScholarBank@NUS Repository.
dc.identifier.issn09574158
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/61710
dc.description.abstractThe application and extension of suitable techniques for integrating neural network and fuzzy system methodologies to enhance a basic fixed neural network-based nonlinear control strategy with the property of self-organization are investigated. It is shown that by establishing a suitable correspondence between Radial Basis Function networks and fuzzy systems, it is possible to develop a self-organizing controller, utilizing a class of Fuzzified Basis Function Networks (FBFN), that autonomously organizes its network structure to the required size and parameters. The effectiveness of the proposed self-organizing FBFN control system is demonstrated in real-time implementation experiments for position control in a servomechanism with asymmetrical loading and changes in the load. © 1995.
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentELECTRICAL ENGINEERING
dc.description.sourcetitleMechatronics
dc.description.volume5
dc.description.issue6
dc.description.page695-713
dc.description.codenMECHE
dc.identifier.isiutNOT_IN_WOS
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