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|Title:||A self-organizing fuzzified basis function network control system applicable to nonlinear servomechanisms||Authors:||Lee, T.H.
|Issue Date:||Sep-1995||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.||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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