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.
A nonparametric ide ...
DETAILS
Nonparametric identification of nonlinear dynamic systems
Dissertationsschrift
Kenderi, Gábor
Kartoniert, 241 S.
graph. Darst.
Sprache: Englisch
24 cm
ISBN-13: 978-3-7315-0834-2
Titelnr.: 75004733
Gewicht: 585 g
KIT Scientific Publishing (2018)
Karlsruher Institut für Technologie (KIT Scientific Publishing c/o KIT-Bibliothek
Straße am Forum 2
76131 Karlsruhe, Baden
info@ksp.kit.edu