Please use this identifier to cite or link to this item:
https://scholarbank.nus.edu.sg/handle/10635/61710
DC Field | Value | |
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dc.title | A self-organizing fuzzified basis function network control system applicable to nonlinear servomechanisms | |
dc.contributor.author | Lee, T.H. | |
dc.contributor.author | Nie, J.H. | |
dc.contributor.author | Tan, W.K. | |
dc.date.accessioned | 2014-06-17T06:43:07Z | |
dc.date.available | 2014-06-17T06:43:07Z | |
dc.date.issued | 1995-09 | |
dc.identifier.citation | Lee, 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.issn | 09574158 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/61710 | |
dc.description.abstract | The 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.source | Scopus | |
dc.type | Article | |
dc.contributor.department | ELECTRICAL ENGINEERING | |
dc.description.sourcetitle | Mechatronics | |
dc.description.volume | 5 | |
dc.description.issue | 6 | |
dc.description.page | 695-713 | |
dc.description.coden | MECHE | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Staff Publications |
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