The PID-type fuzzy neural network control and it´s application in the hydraulic turbine generators

Author

Yin-Song, Wang ; Guo-Cai, Shang ; Tong-Xiang, He

Author_Institution

North China Electr. Power Univ., Boadmg, China

Volume

1

fYear

2000

fDate

2000

Firstpage

338

Abstract

In this paper, a fuzzy-neural-networks (FNN) scheme based on the gradient descent algorithm is proposed for a PID-type fuzzy controller. The proposed FNN is utilized in the self-learning control structure. In the control system, the proposed FNN as feedback a controller (FNNC). The authors give and analyze the convergent theorem that guarantees the learning rate to converge for the FNNC. For hydraulic turbine generators, the online learning ability of the proposed FNNC is confirmed by computer simulation results

Keywords

control system analysis computing; control system synthesis; electric machine analysis computing; feedback; fuzzy control; fuzzy neural nets; hydroelectric generators; machine control; machine theory; neurocontrollers; three-term control; turbogenerators; unsupervised learning; PID-type fuzzy neural network control; computer simulation; control design; control simulation; controller feedback; convergent theorem; gradient descent algorithm; hydraulic turbine generators; learning rate; online learning ability; self-learning control structure; Control systems; Error correction; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Hydraulic turbines; Intelligent networks; Neural networks; Neurons;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Engineering Society Winter Meeting, 2000. IEEE

Print_ISBN

0-7803-5935-6

Type

conf

DOI

10.1109/PESW.2000.849985

Filename

849985