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  • 标题:Robust-Neural Observer Design for Discrete-Time Uncertain Non-Affine Nonlinear System
  • 本地全文:下载
  • 作者:Somayeh Rahimi ; Saeed Mohammad-Hoseini
  • 期刊名称:International Journal of Electrical and Computer Engineering
  • 电子版ISSN:2088-8708
  • 出版年度:2014
  • 卷号:4
  • 期号:4
  • 页码:603-613
  • DOI:10.11591/ijece.v4i4.6171
  • 语种:English
  • 出版社:Institute of Advanced Engineering and Science (IAES)
  • 摘要:This paper proposed a new Nonlinear Discrete-Time Robust-Neural Observer (DTRNO) which capable to give estimation for the states of Discrete-Time Uncertain Non-affine Non-linear Systems in presence of external disturbances. The Neural network is a kind of discrete-time Multi Layered Perceptron (MLP) which Trained with an Extended Kalman-Filter (EKF) based algorithm, which this neural observer is robust in presence of external and internal uncertainties, using a parallel configuration.This work includes the stability proof of the estimation error on the basis of the Lyapunov approach, and for demonstrate observer performance an Uncertain Non-affine Nonlinear Systems have been simulated to formulations validate the theoretical. Simulation results confirm the proficiency of the DTRNO even at the different operating conditions and presence of parameters uncertainties.
  • 关键词:Robust-Neural,Observer,Discrete-TimeNonlinear,Neural State Estimation,Multi Layered Perceptron ,Extended Kalman-Filter
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