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Author:

Song, Y. (Song, Y..) | Zhang, C. (Zhang, C..) (Scholars:张弛) | Ma, W. (Ma, W..)

Indexed by:

Scopus PKU CSCD

Abstract:

In this paper a novel parameter identification method for linear system is developed based on the optimization computing theory of Hopfield Neural Networks(HNN). The I/O difference equation is formulated and estimated using continuous HNN firstly. Then the transfer function matrix of the system is calculated. And finally the observable canonical form of the state space expression is constructed. Simulation results prove the validity of the proposed method.

Keyword:

Hopfield neural networks(HNN); Linear system; Parameter identification

Author Community:

  • [ 1 ] [Song, Y.]School of Mechanical and Electrical Engineering, Beijing Polytechnic University, Beijing, 100022, China
  • [ 2 ] [Zhang, C.]School of Mechanical Engineering, Tianjin University, Tianjin, 300072, China
  • [ 3 ] [Ma, W.]Department of Automation, Tianjin Institute of Textile Engineering, Tianjin, 300160, China

Reprint Author's Address:

  • [Song, Y.]School of Mechanical and Electrical Engineering, Beijing Polytechnic University, Beijing, 100022, China

Email:

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Source :

Control Theory and Applications

ISSN: 1000-8152

Year: 2000

Issue: 1

Volume: 17

Page: 121-124

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 7

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