Power system stabilization using fuzzy-neural hybrid intelligent control

Author

Ko, Hee-Sang ; Niimura, T.

Author_Institution

Dept. of Electr. & Comput. Eng., British Columbia Univ., Canada

fYear

2002

fDate

2002

Firstpage

879

Lastpage

884

Abstract

This paper presents fuzzy-neural hybrid control for power system stabilization. The main idea of hybrid control is that the dynamic feedforward compensator can be used for improving the ability to track the reference rather than changing the dynamics, while feedback is used for stabilizing the system and for suppressing disturbances. In this paper, fuzzy logic is applied to design a feedback controller and then a neural network inverse model is obtained for a feedforward compensator. The controller is tested for a one-machine infinite-bus power system under various operating conditions.

Keywords

control system synthesis; feedback; feedforward neural nets; fuzzy control; inverse problems; neurocontrollers; power system control; power system stability; disturbance suppression; dynamic feedforward compensator; feedback; feedback controller; fuzzy logic; fuzzy-neural hybrid intelligent control; neural network inverse model; one-machine infinite-bus power system; power system stabilization; reference tracking; two layer neural network; Adaptive control; Control systems; Fuzzy logic; Hybrid power systems; Intelligent control; Neurofeedback; Power system control; Power system dynamics; Power system modeling; Power systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control, 2002. Proceedings of the 2002 IEEE International Symposium on

ISSN

2158-9860

Print_ISBN

0-7803-7620-X

Type

conf

DOI

10.1109/ISIC.2002.1157878

Filename

1157878