Title :
The Study of Adaptive Control of Hydraulic Generator Unit by Using GA-Improved Wavelet Neural Networks
Author :
Hong, Zhao ; Mi, Yanhua
Author_Institution :
Sch. of Mechatron. Eng., China Jiliang Univ., Hangzhou, China
Abstract :
Due to the highly complex dynamics of hydraulic generator unit, it is hard to develop an accurate analytical expression of the dynamic model, a new adaptive control algorithm based on the learning characteristic of neural network and the function approximation ability of the wavelet is presented in this paper. The control system consists of two wavelet networks, one realizes active identification and another control for hydraulic generator unit. Simulation results show that this control system is more effective than those based on neural networks.
Keywords :
adaptive control; function approximation; genetic algorithms; hydraulic systems; hydroelectric generators; neurocontrollers; wavelet transforms; GA-improved wavelet neural networks; adaptive control algorithm; function approximation; genetic algorithm; hydraulic generator unit; GA-improved wavelet; control; hydraulic generator unit; neural networks;
Conference_Titel :
Digital Manufacturing and Automation (ICDMA), 2010 International Conference on
Conference_Location :
ChangSha
Print_ISBN :
978-0-7695-4286-7
DOI :
10.1109/ICDMA.2010.36