Fuzzy logic control of dynamic quadrature booster using reinforcement learning

Author

Li, B.H. ; Wu, Q.H. ; Wang, P.Y. ; Zhou, X.X.

Author_Institution

Electr. Power Res. Inst., Beijing, China

Volume

2

fYear

1998

fDate

18-21 Aug 1998

Firstpage

843

Abstract

This paper is concerned with the investigation of a learning fuzzy logic control of dynamic quadrature booster (DQB) to enhance power system stability. A fuzzy logic control strategy is proposed for DQB control and a reinforcement learning technique is employed to optimise the parameters of the fuzzy logic controller according to a given performance index. The parameter optimisation is carried out on-line in real time. Simulation results show a satisfactory learning and control performance provided by this strategy

Keywords

fuzzy control; learning (artificial intelligence); learning automata; optimisation; power system control; power system stability; dynamic quadrature booster; fuzzy logic control; learning fuzzy logic control; parameters optimisation; performance index; power system stability enhancement; reinforcement learning; Control systems; Fuzzy logic; Learning; Optimal control; Power system control; Power system dynamics; Power system modeling; Power system simulation; Power system stability; Power systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Power System Technology, 1998. Proceedings. POWERCON '98. 1998 International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-4754-4

Type

conf

DOI

10.1109/ICPST.1998.729204

Filename

729204