Application of wavelets neural network in superheated temperature control system

Author

Liu, Wending ; Yan, Wen ; Kan, Jiangming ; Li, Yongchao

Author_Institution

Autom. Dept., Beijing Forestry Univ., Beijing, China

Volume

3

fYear

2010

fDate

10-12 Aug. 2010

Firstpage

1357

Lastpage

1359

Abstract

This paper combines merits of internal model control, such as simple design, good regulation capacity, high robustness and the ability to eliminate the unknown disturbance, to construct a internal model control system based on wavelets neural network, which is characterized by high robustness and quick response speed and then it can bring good control performance when controlled objects vary in a wide range. Finally, it is triumphantly used in simulation of the 1st superheated steam temperature reduction control system of 500MW units and good performances are obtained.

Keywords

heat transfer; neural nets; steam; temperature control; wavelet transforms; internal model control; power 500 MW; superheated steam temperature reduction control system; superheated temperature control system; wavelets neural network; Adaptation model; Algorithm design and analysis; Approximation methods; Artificial neural networks; Load modeling; Temperature control; back-propagate algorithm; internal model control; the boiler superheated steam temperature; wavelets neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation (ICNC), 2010 Sixth International Conference on

Conference_Location

Yantai, Shandong

Print_ISBN

978-1-4244-5958-2

Type

conf

DOI

10.1109/ICNC.2010.5582733

Filename

5582733