In this paper, a nonlinearity compensation strategy for matrix converter is investigated.
研究了一种矩阵变换器的非线性补偿方法。
The principle of nonlinearity compensation and training method of neural network are introduced.
介绍了非线性补偿的原理和网络训练方法。
The test result shows that online learning can make nonlinearity compensation for controlled object, so as to system has better self-adoption and robustness.
实验表明经在线学习补偿被控对象的非线性，使系统具有较强的自适应和鲁棒性。
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