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A Radial Basis Function Neural Networks Based Space-Vector PWM Controller for Voltage-Fed Inverter
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| Author(s) |
Yuxiang ZHAN, Yanfeng CHEN, Bo ZHANG, Jianzhuang CHEN |
| Abstract |
In this paper, the basic principle of space-voltage vector PWM (SVPWM) is presented. Due to backpropagation neural networks (BP) based SVPWM controller have local optimization problem andlower training rate, a radial basis function neural networks (RBF) controller based SVPWM isproposed. Using Matlab/Simulink together with Neural Network Toolbox, we develop a computersimulation program for the RBF-SVPWM Inverter. The results indicate that the RBF-SVPWMInverter generates less current harmonic distortion than BP- SVPWM Inverter and the traditionalSVPWM Inverter. |
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| Filename: | 0332-epe2014-full-11020994.pdf |
| Filesize: | 225.2 KB |
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| Type |
Members Only |
| Date |
Last modified 2015-06-08 by System |
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