Neuro-fuzzy power system stabiliser

N. Hosseinzadeh, A. Kalam

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

A fuzzy logic power system stabiliser has been developed using speed and active power deviations as the controller input variables. The inference mechanism of the fuzzy logic controller is represented by a 7 × 7 decision table, i.e. 49 if-then rules. In order to use it under a wide range of operating conditions, its parameters have been tuned using a neural network. The tuned stabiliser has been tested by performing non-linear simulations using a synchronous machine-infinite bus model. It is shown that the neuro-fuzzy stabiliser is superior to a fixed parameter fuzzy logic power system stabiliser.

Original languageEnglish
Title of host publicationIECON Proceedings (Industrial Electronics Conference)
Editors Anon
Pages608-612
Number of pages5
Volume1
Publication statusPublished - 1996
EventProceedings of the 1996 IEEE 22nd International Conference on Industrial Electronics, Control, and Instrumentation, IECON. Part 3 (of 3) - Taipei, Taiwan
Duration: Aug 5 1996Aug 10 1996

Other

OtherProceedings of the 1996 IEEE 22nd International Conference on Industrial Electronics, Control, and Instrumentation, IECON. Part 3 (of 3)
CityTaipei, Taiwan
Period8/5/968/10/96

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ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Hosseinzadeh, N., & Kalam, A. (1996). Neuro-fuzzy power system stabiliser. In Anon (Ed.), IECON Proceedings (Industrial Electronics Conference) (Vol. 1, pp. 608-612)