Nonparametric identification of nonlinear dynamic systems : Dissertationsschrift

ISBN-13: 9783731508342 / Angielski / Miękka / 2018 / 241 str.

Gábor Kenderi

Opis

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.