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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| 245 | 1 | 0 | |a Nonparametric identification of nonlinear dynamic systems |
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| 490 | 1 | |a Schriftenreihe des Instituts für Technische Mechanik, Karlsruher Institut für Technologie | |
| 520 | |a 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. | ||
| 546 | |a English | ||
| 653 | |a nichtlineare dynamische System | ||
| 653 | |a Kalman Filter | ||
| 653 | |a nonlinear dynamic system | ||
| 653 | |a nonparametric identification | ||
| 653 | |a nichtparametrische Identifikation | ||
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