Power system stabilization using fuzzy-neural hybrid intelligent control

TitlePower system stabilization using fuzzy-neural hybrid intelligent control
Publication TypeConference Paper
Year of Publication2002
AuthorsKo, H. - S., and T. Niimura
Conference NameIntelligent Control, 2002. Proceedings of the 2002 IEEE International Symposium on
Pagination879 - 884
Keywordscontrol system synthesis, disturbance suppression, dynamic feedforward compensator, feedback, feedback controller, feedforward neural nets, fuzzy control, fuzzy logic, fuzzy-neural hybrid intelligent control, inverse problems, neural network inverse model, neurocontrollers, one-machine infinite-bus power system, power system control, power system stability, power system stabilization, reference tracking, two layer neural network

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.


a place of mind, The University of British Columbia

Electrical and Computer Engineering
2332 Main Mall
Vancouver, BC Canada V6T 1Z4
Tel +1.604.822.2872
Fax +1.604.822.5949

Emergency Procedures | Accessibility | Contact UBC | © Copyright 2021 The University of British Columbia