Title :
Study on simulation model of switched reluctance startor/generator system based on wavelet neural network
Author :
Xiaoshu Zan ; Fangnan Xie
Abstract :
This paper presents a novel integrated simulation model of switched reluctance startor/generator system based on wavelet neural network. The switched reluctance startor/generator system is hard to obtain good simulation model due to its critical nonlinearity. Relatively accurate mathematical model would be built by the wavelet neural network due to its powerful learning, approximation and prediction abilities. The nonlinear mapping relation of the flux-linkage, current and rotor position has been realized by the wavelet neural network and the simulation model of switched reluctance startor/generator system is established meanwhile. The simulation has high operation speed and can be modified conveniently. The effectiveness of the proposed simulation model has been confirmed both by simulation and experiment results.
Keywords :
neural nets; power engineering computing; reluctance generators; wavelet transforms; flux-linkage; mathematical model; nonlinear mapping relation; simulation model; switched reluctance stator-generator system; wavelet neural network; Biological neural networks; Couplings; Generators; Mathematical model; Power generation; Pulse width modulation; Switches;
Conference_Titel :
Advanced Mechatronic Systems (ICAMechS), 2011 International Conference on
Conference_Location :
Zhengzhou
Print_ISBN :
978-1-4577-1698-0