计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (31): 87-89.

• 学术探讨 • 上一篇    下一篇

基于Elman神经网络的非线性动态系统辨识

高钦和1,2,王孙安1   

  1. 1.西安交通大学 机械工程学院,西安 710028
    2.第二炮兵工程学院,西安 710025
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-11-01 发布日期:2007-11-01
  • 通讯作者: 高钦和

Identification of nonlinear dynamic system based on Elman neural network

GAO Qin-he1,2,WANG Sun-an1   

  1. 1.School of Mechanical Engineering,Xi’an Jiaotong University,Xi’an 710028,China
    2.Second Artillery Engineering College,Xi’an 710025,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-11-01 Published:2007-11-01
  • Contact: GAO Qin-he

摘要: 研究了应用动态递归神经网络实现动态系统辨识的原理和方法,在没有被辨识对象的先验知识情况下,通过改进的Elman网络实现了非线性动态系统的辨识。仿真结果表明,与前馈网络相比,Elman网络具有学习速度快、泛化能力强的特点,可用较小的网络结构实现高阶系统的辨识,适用于具有本质非线性动态系统的辨识。

Abstract: The theory and method of dynamic system identification by dynamic recurrent neural network are studied.An improved Elman neural network is successfully used to identify the nonlinear dynamic system even though without any prior information of identified system.Simulation results show that the Elman neural network has higher learning speed and better generalization ability than the feedforward neural network,and that it is suitable for the nonlinear dynamic system identification.