摘要
单相逆变电源的输出电压波形质量是衡量其性能的重要指标之一.本文提出了一种正弦逆变波形的神经网络内膜控制算法,建立两个BP神经网络预估器,一个作为单相逆变器的内部模型,预测实际的波形输出;一个根据预测误差建立内模控制器,在线修正和补偿内部模型使之最大程度的匹配单相逆变器.仿真和实验结果表明,该算法克服了系统中存在的不确定性,有效的提高了系统的逆变波形质量和负载适应性.
The quality of output waveform is one important factor for the single-phase inverter. This paper proposed the algo- rithm based on neural network internal model theory, which is used for an output sine waveform control. Based on this control algo- rithm,two back propagation estimate neural networks were established. One is the internal model of single-phase inverter, which is used to estimate the actual output waveform. The other one is used to make the internal model to fit the actual single-phase inverter due to the estimate en＇or. We finished the simulation and experiment, where the algorithm was proved that it could improve the out- put waveform quality and load compatibility.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2012年第7期1345-1350,共6页
Acta Electronica Sinica
基金
住房和城乡建设部科学技术研究开发项目(No.2008-k6-22)
关键词
单相逆变电源
内模原理
BP神经网络
波形控制
single-phase inverter
internal model theory
back propagation neural network
waveform control
