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System identification in hydraulic servo system with diagonal recurrent neural networks

机译:对角复发神经网络液压伺服系统中的系统识别

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This paper points out that the Diagonal Recurrent Neural Networks (DRNN) can deal with the dynamical system more effectively. We use this neural networks to identify the hydraulic servo system dynamical performance The adjustment of weight is the algorithm that take time varied into account. The simulation results and experiments testified that this method could rapidly and exactly get the dynamical performance.
机译:本文指出,对角线经常性神经网络(DRNN)可以更有效地处理动态系统。我们使用这种神经网络来识别液压伺服系统动态性能,调整权重是花费时间变化的算法。仿真结果和实验证明了这种方法可以迅速,完全得到动力学性能。

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