DocumentCode :
2541030
Title :
Neural network model predict control for the hydroturbine generator set
Author :
Chang, Jiang ; Xiao, Zhi-huai ; Wang, Shu-qing
Author_Institution :
Dept. of Mech. & Electr. Eng., ShenZhen Polytech, China
Volume :
1
fYear :
2003
fDate :
2-5 Nov. 2003
Firstpage :
540
Abstract :
Due to the complex nonlinear characteristic of hydroturbine generator set (HTGS), this paper proposes the neural network model predict control (NNMPC) for the HTGS. The NNMPC uses a neural network model to predict future HTGS response to potential control signals. An optimization algorithm then computes the control signals that optimize future HTGS performance. Simulation results show that NNMPC is an effective tool for the HTGS.
Keywords :
neurocontrollers; predictive control; turbogenerators; control signals; hydroturbine generator set; neural network model predict control; Computational modeling; Electronic mail; Frequency; Jacobian matrices; Neural networks; Newton method; Power engineering; Power generation; Power system dynamics; Predictive models;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
Type :
conf
DOI :
10.1109/ICMLC.2003.1264536
Filename :
1264536
Link To Document :
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