Artificial neural networks controlled fast valving in a power generation plant

Author

Han, Yingduo ; Xiu, Lincheng ; Wang, Zhonghong ; Chen, Qi ; Tan, Shaohua

Author_Institution

Dept. of Electr. Eng., Tsinghua Univ., Beijing, China

Volume

8

Issue

2

fYear

1997

fDate

3/1/1997 12:00:00 AM

Firstpage

373

Lastpage

389

Abstract

This paper presents an artificial neural-network-based controller to realize the fast valving in a power generation plant. The backpropagation algorithm is used to train the feedforward neural networks controller. The hardware implementation and the test results of the controller on a physical pilot-scale power plant setup are described in detail. Compared with the conventional fast valving methods applied to the same system, test results both with the computer simulation and on a physical pilot-scale power plant setup demonstrate that the artificial neural network controller has satisfactory generalization capability, reliability, and accuracy to be feasible for this critical control operation

Keywords

backpropagation; feedforward neural nets; neurocontrollers; nonlinear control systems; power system control; artificial neural-network-based controller; backpropagation algorithm; computer simulation; fast valving; feedforward neural networks controller; generalization capability; hardware implementation; pilot-scale power plant; power generation plant; reliability; Artificial neural networks; Backpropagation algorithms; Computer network reliability; Computer simulation; Feedforward neural networks; Hardware; Neural networks; Power generation; Power system reliability; System testing;

fLanguage

English

Journal_Title

Neural Networks, IEEE Transactions on

Publisher

ieee

ISSN

1045-9227

Type

jour

DOI

10.1109/72.557689

Filename

557689