基于人工神经网络的空间矢量PWM逆变器研究

Zhi Yuan, Jiaguang Cheng
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引用次数: 2

摘要

本文提出了一种基于人工神经网络的电压源逆变器空间矢量PWM算法。在计算逆变器三相导通时间时,本文采用三层前馈网络,采用Levenberg-Marquarde算法对网络进行训练。该方法利用人工神经网络强大的非线性逼近能力,避免了大量的非线性计算。最后,在MATLAB/Simulink环境下,建立了系统的仿真模型。仿真结果表明,人工神经网络的SVPWM算法可以提高开关频率,降低输出电压和电流的谐波。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Space Vector PWM Inverter Based on Artificial Neural Network
This paper proposed a Space Vector PWM algorithm based on artificial neural network for voltage-source inverters. When calculating the invert's three-phase turn-on time, the paper uses a three-layer forward-feed network which adopts the algorithm of Levenberg-Marquarde to train the network. This method uses artificial neural network's strong nonlinear approximation ability to avoid a lot of nonlinear calculation. At last, in the environment of MATLAB/Simulink, simulation model of the system was built. The simulation results show that the SVPWM algorithm of artificial neural network can improve the switching frequency and reduce the harmonic of output voltage and current.
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