Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/61710
Title: A self-organizing fuzzified basis function network control system applicable to nonlinear servomechanisms
Authors: Lee, T.H. 
Nie, J.H. 
Tan, W.K. 
Issue Date: Sep-1995
Source: 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.
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.
Source Title: Mechatronics
URI: http://scholarbank.nus.edu.sg/handle/10635/61710
ISSN: 09574158
Appears in Collections:Staff Publications

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