NDLI: Free-model based neural network for dynamic systems

Content Provider	IEEE Xplore Digital Library
Author	Chi-Li-Ma Harnold Lee, K.Y. Jin-Ho Lee Young-Moon Park
Copyright Year	1999
Description	Author affiliation: Dept. of Electr. Eng., Pennsylvania State Univ., University Park, PA, USA (Chi-Li-Ma Harnold)
Abstract	An approach to identify and control an unknown nonlinear dynamic system using the free-model based neural network is discussed. The free model for an unknown system is further derived and approximation errors between real and approximated outputs are briefly discussed. Applying the free-model preprocessed inputs to the neural network, the free-model based neural network is trained to approximate the output for the unknown system. Since the free-model input preprocessing can be viewed as a high pass filter, the free-model based neural network converges faster than the conventional neural network representation. The free-model based neural networks are implemented in a model reference adaptive inverse control scheme which is applied to a nonlinear plant with satisfactory performance.
Starting Page	2819
Ending Page	2823
File Size	439011
Page Count	5
File Format	PDF
ISBN	0780349903
ISSN	07431619
DOI	10.1109/ACC.1999.786586
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-06-02
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	American Automatic Control Council(AACC)
Subject Keyword	Neural networks Nonlinear dynamical systems Data preprocessing Nonlinear control systems Control systems Approximation error Filters Inverse problems Programmable control Adaptive control
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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