DocumentCode :
389279
Title :
A modified neuron model-free controller with PID turning gain for hydroelectric generating units
Author :
Zhang, Jian-ming ; Wang, Shu-Qing
Author_Institution :
Res. Inst. of Adv. Process Control, Zhejiang Univ., Hangzhou, China
Volume :
2
fYear :
2002
fDate :
2002
Firstpage :
784
Abstract :
A new neuron model-free control method for hydroelectric generating units is applied with consideration of the intrinsic characteristics of hydroelectric generating units and the problem with the governing control. The influences of time-varying parameters and the disturbances on control behavior of the system are eliminated by the use of a neuron model-free control method with PID turning gain. Simulation results show that the new control system has good real-time control performance and strong learning ability. The transient and robust performances of the governing system are improved markedly. The control requirements can be matched under variations of the water turbine governing system structure and parameters.
Keywords :
adaptive control; control system synthesis; hydroelectric generators; learning (artificial intelligence); neurocontrollers; nonlinear control systems; power generation control; robust control; three-term control; time-varying systems; transient response; PID turning gain; adaptive neuron model; control behavior disturbances; governing control; hydroelectric generating units; intelligent control; intrinsic characteristic; learning ability; neuron model-free controller; nonlinear parameters; real-time control performances; robust performance; simulation study; time-varying parameters; transient performance; water turbine governing system structure; Character generation; Control system synthesis; Control systems; Hydroelectric power generation; Neurons; Real time systems; Robustness; Three-term control; Time varying systems; Turning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on
Print_ISBN :
0-7803-7508-4
Type :
conf
DOI :
10.1109/ICMLC.2002.1174488
Filename :
1174488
Link To Document :
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