Application of neural network to real time tuning of fuzzy logic PSS

Author

Hiyama, Takashi

Author_Institution

Dept. of Electr. Eng. & Comput. Sci., Kumamoto Univ., Japan

fYear

1993

fDate

1993

Firstpage

421

Lastpage

426

Abstract

A fuzzy logic power system stabilizer is proposed, and a neural network is utilized for its real time tuning to keep its performance optimal under wider ranges of operating conditions. Simulation results show the efficiency of the proposed real time tuning of the fuzzy logic power system stabilizer by the neural network. The proposed fuzzy logic power system stabilizer can be configured by using a microcomputer and an A/D and a D/A conversion boards, and easily implemented in power systems.

Keywords

fuzzy control; fuzzy logic; microcomputer applications; neural nets; optimal control; power system computer control; power system stability; real-time systems; ADC; DAC; PSS; digital control; fuzzy control; fuzzy logic; microcomputer; neural network; optimal control; performance; power system stabilizer; real time tuning; Acceleration; Application software; Computational modeling; Fuzzy logic; Neural networks; Power generation; Power system simulation; Power system stability; Real time systems; Sampling methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks to Power Systems, 1993. ANNPS '93., Proceedings of the Second International Forum on Applications of

Conference_Location

Yokohama, Japan

Print_ISBN

0-7803-1217-1

Type

conf

DOI

10.1109/ANN.1993.264311

Filename

264311