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

LIU Heping; ZHANG Lanling; SUN Yikang

doi:10.13374/j.issn1001-053x.2000.02.026

Volume 22 Issue 2

Aug. 2021

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Article Navigation > Chinese Journal of Engineering > 2000 > 22(2): 190-192

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

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

doi: 10.13374/j.issn1001-053x.2000.02.026

Information Engineering School, UST Beijing, Beijing 100083, China

Received Date: 1999-07-15
Available Online: 2021-08-27

Abstract

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.
- multivariable nonlinear system,
- multilayer local recurrent neural networks,
- multistep predictive modeling,
- Jocobian matrixs