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Nonparametric identification of nonlinear dynamic systems

Author: Kenderi, Gábor
Source: Directory of Open Access Books
Publisher: KIT Scientific Publishing
ISBN: 9783731508342
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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.