Nonparametric identification of nonlinear dynamic systems
Résumé
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.
Keywords
nichtlineare dynamische System; Kalman Filter; nonlinear dynamic system; nonparametric identification; nichtparametrische IdentifikationISBN
9783731508342Publisher
KIT Scientific PublishingPublisher website
http://www.ksp.kit.edu/Publication date and place
2018Series
Schriftenreihe des Instituts für Technische Mechanik, Karlsruher Institut für Technologie,Classification
Technology: general issues