Title :
Adaptive-network-based fuzzy logic power system stabilizer
Author :
Hariri, A. ; Malik, O.P.
Author_Institution :
Dept. of Electr. & Comput. Eng., Calgary Univ., Alta., Canada
Abstract :
An adaptive network-based fuzzy logic power system stabilizer (ANF PSS) is presented in this paper. This method combines the advantages of artificial neural networks (ANNs) and fuzzy logic control (FLC) schemes together to design a new PSS. In this approach, a fuzzy logic based PSS with learning ability has been constructed and is trained directly from the input and the output of the generating unit. The proposed PSS employs a multilayer adaptive network with the error backpropagation training method. Results show that the proposed ANF PSS can provide good damping of the power system over a wide range and significantly improve the dynamic performance of the system
Keywords :
adaptive control; backpropagation; control system synthesis; fuzzy control; fuzzy neural nets; neurocontrollers; power system control; power system stability; adaptive fuzzy control scheme; artificial neural networks; control design; damping; dynamic performance; error backpropagation training method; fuzzy logic control; learning ability; multilayer adaptive network; power system stabilizer; Adaptive systems; Artificial neural networks; Control system synthesis; Control systems; Damping; Fuzzy logic; Power system dynamics; Power system modeling; Power system stability; Power systems;
Conference_Titel :
WESCANEX 95. Communications, Power, and Computing. Conference Proceedings., IEEE
Conference_Location :
Winnipeg, Man.
Print_ISBN :
0-7803-2725-X
DOI :
10.1109/WESCAN.1995.493955