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...
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| Superior document: | Schriftenreihe des Instituts für Technische Mechanik, Karlsruher Institut für Technologie |
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| Year of Publication: | 2018 |
| Language: | English |
| Series: | Schriftenreihe des Instituts für Technische Mechanik, Karlsruher Institut für Technologie
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| Physical Description: | 1 electronic resource (XXVIII, 194 p. p.) |
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| Summary: | 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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| ISBN: | 1000085419 |
| Hierarchical level: | Monograph |