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...
Furkejuvvon:
| Váldodahkki: | |
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| Materiálatiipa: | Elektrovnnalaš Girjji oassi |
| Giella: | eaŋgalasgiella |
| Almmustuhtton: |
KIT Scientific Publishing
2018
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| Ráidu: | Schriftenreihe des Instituts für Technische Mechanik, Karlsruher Institut für Technologie
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| Fáttát: | |
| Liŋkkat: | DOAB: download the publication DOAB: description of the publication |
| Fáddágilkorat: |
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| Čoahkkáigeassu: | 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. |
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| Olgguldas hápmi: | 1 electronic resource (XXVIII, 194 p. p.) |
| ISBN: | KSP/1000085419 9783731508342 |
| Beassan: | Open Access |