Title :
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
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;
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
DOI :
10.1109/ICNC.2010.5582733
