刘贺平, 张兰玲, 孙一康. 多层局部回归网络的非线性系统预测模型[J]. 工程科学学报, 2000, 22(2): 190-192. DOI: 10.13374/j.issn1001-053x.2000.02.026
引用本文: 刘贺平, 张兰玲, 孙一康. 多层局部回归网络的非线性系统预测模型[J]. 工程科学学报, 2000, 22(2): 190-192. DOI: 10.13374/j.issn1001-053x.2000.02.026
LIU Heping, ZHANG Lanling, SUN Yikang. Multistep Predictive Modeling of Nonlinear System Based on Multilayer Local Recurrent Neural NetWorks[J]. Chinese Journal of Engineering, 2000, 22(2): 190-192. DOI: 10.13374/j.issn1001-053x.2000.02.026
Citation: LIU Heping, ZHANG Lanling, SUN Yikang. Multistep Predictive Modeling of Nonlinear System Based on Multilayer Local Recurrent Neural NetWorks[J]. Chinese Journal of Engineering, 2000, 22(2): 190-192. DOI: 10.13374/j.issn1001-053x.2000.02.026

多层局部回归网络的非线性系统预测模型

Multistep Predictive Modeling of Nonlinear System Based on Multilayer Local Recurrent Neural NetWorks

  • 摘要: 提出采用多层局部回归神经网络建立多变量非线性系统多步预测模型的方法,神经网络模型可提供多步预测控制所需要的系统输出预测值及输出向量对控制向量的雅可比矩阵.仿真试验表明这种动态神经网络的预测模型具有较高的精度.

     

    Abstract: The multistep predictive modeling of MIMO nonlinear system based on multilayer local recurrent neural networks is presented. The predictive outputs and Jocobian matrixs of output vecter versus input vecter are proffered by the neural networks predictive model for the multistep predictive control systems. The results of simulation show that predictive model of the dynamic neural networks can reach higher degree of accuracy.

     

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