北京航空航天大学学报 ›› 2003, Vol. 29 ›› Issue (3): 248-251.

• 论文 • 上一篇    下一篇

基于对角回归网络的非线性系统建模

陈平, 裘丽华, 王占林   

  1. 北京航空航天大学 自动化科学与电气工程学院
  • 收稿日期:2001-10-10 出版日期:2003-03-31 发布日期:2010-09-27
  • 作者简介:陈 平(1974-),男,江西南昌人,博士生,100083,北京.

Modeling of Nonlinear System with Diagonal Recurrent Neural Network

Chen Ping, Qiu Lihua, Wang Zhanlin   

  1. School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics
  • Received:2001-10-10 Online:2003-03-31 Published:2010-09-27

摘要: 分析了非线性系统神经网络建模的规律,利用对角回归神经网络(DRNN)实现了非线性动态系统的辨识.辨识结构采用串并联模式,网络权值的调整为考虑时变因素的调整算法.与静态神经网络相比,基于DRNN的辨识方法显示出很强的处理动态问题的能力,无需辨别系统阶次,辨识结构简单,收敛速度快.仿真结果表明该方法是有效可行的.

Abstract: Based on an analysis on the modeling principles of nonlinear system, the identification of a nonlinear system was realized with Diagonal Recurrent Neural Networks (DRNN). Serial-parallel identification architecture was applied in the modeling. Time variation was taken into account in the adjustment algorithm of weights. Compared with static neural network, the method based on DRNN displays better ability to deal with a dynamic system, due to its advantages such as without the need of system order number, a smaller neural network structure and a faster convergence. Simulation results testified the feasibility and validity of the proposed method.

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