DocumentCode :
2472513
Title :
PID neural network decoupling control for doubly fed hydro-generator system
Author :
Guo, Aiwen ; Yang, Jiandong ; Bao, Haiyan
Author_Institution :
State Key Lab. of Water Resources & Hydropower Eng. Sci., Wuhan Univ., Wuhan
fYear :
2008
fDate :
25-27 June 2008
Firstpage :
6149
Lastpage :
6152
Abstract :
Proportional, integral and differential are defined as a neuron respectively, combined with neural network in this paper. PID neural network (PIDNN) is built and the structure of PIDNN is also simple. Using the PID neural network, the strong coupled time-varying system can be decoupled and controlled easily. The doubly fed hydro-generator system is a novel type of hydraulic generation system. Considering the performances of uncertain and nonlinear as well as parameters coupling and time-variation for three parts of water flux, hydro-turbine and generator, the PIDNN control strategy is introduced. By comparison with the conventional PID control, the results of simulation show that hydro-generator system is good robustness against system parameters uncertainly and load disturbance.
Keywords :
hydroelectric generators; machine control; neurocontrollers; nonlinear control systems; robust control; three-term control; time-varying systems; uncertain systems; PID neural network decoupling control; doubly fed hydro-generator system; hydraulic generation system; hydro-turbine generator; nonlinear system; robustness; time-varying system; uncertain system; water flux; Control systems; Frequency; Induction generators; Neural networks; Neurons; Power engineering and energy; Power system stability; Robust control; Rotors; Three-term control; PID neural network; decoupling control; doubly fed hydrogenerator system; simulation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
Type :
conf
DOI :
10.1109/WCICA.2008.4592788
Filename :
4592788
Link To Document :
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