Title :
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
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;
Conference_Titel :
Power Engineering Society Winter Meeting, 2000. IEEE
Print_ISBN :
0-7803-5935-6
DOI :
10.1109/PESW.2000.849985
