Nonparametric identification of nonlinear dynamic systems

Nonparametric identification of nonlinear dynamic systems

A nonparametric identification method for highly nonlinear systems is presented that is able to reconstruct the underlying nonlinearities without a priori knowledge of the describing nonlinear functions. The approach is based on nonlinear Kalman Filter algorithms using the well-known state augmentat...

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Bibliographic Details
Main Author: Kenderi, Gábor (auth)
Format: Electronic Book Chapter
Language:English
Published: KIT Scientific Publishing 2018
Series:Schriftenreihe des Instituts für Technische Mechanik, Karlsruher Institut für Technologie
Subjects:
Technology: general issues
nichtlineare dynamische System
Kalman Filter
nonlinear dynamic system
nonparametric identification
nichtparametrische Identifikation
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Summary:A nonparametric identification method for highly nonlinear systems is presented that is able to reconstruct the underlying nonlinearities without a priori knowledge of the describing nonlinear functions. The approach is based on nonlinear Kalman Filter algorithms using the well-known state augmentation technique that turns the filter into a dual state and parameter estimator, of which an extension towards nonparametric identification is proposed in the present work.
Physical Description:1 electronic resource (XXVIII, 194 p. p.)
ISBN:KSP/1000085419
9783731508342
Access:Open Access

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