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A fuzzy basis function network for generator excitation control

Abido, M.A. and Abdel-Magid, Y.L. (1997) A fuzzy basis function network for generator excitation control. Fuzzy Systems, 1997., Proceedings of the Sixth IEEE International conference, 3.

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Abstract

A fuzzy basis function network (FBFN) based power system stabilizer (PSS) is presented in this paper. The proposed FBFN based PSS provides a natural framework for combining numerical and linguistic information in a uniform fashion. The proposed FBFN is trained over a wide range of operating conditions in order to re-tune the PSS parameters in real-time based on generator loading conditions. The orthogonal least squares learning algorithm is developed for designing an adequate and parsimonious FBFN model. Time domain simulations of a synchronous machine equipped with the proposed stabilizer subject to major disturbances are investigated. The performance of the proposed FBFN based PSS is compared with that of a conventional power system stabilizer. The results show the robustness of the proposed FBFN PSS and its ability to enhance system damping over a wide range of operating conditions and system parameter variations



Item Type:Article
Date:July 1997
Date Type:Publication
Subjects:Computer
Divisions:College Of Engineering Sciences > Electrical Engineering Dept
Creators:Abido, M.A. and Abdel-Magid, Y.L.
ID Code:14474
Deposited By:KFUPM ePrints Admin
Deposited On:24 Jun 2008 16:37
Last Modified:12 Apr 2011 13:15

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