Identification of general time-varying systems
Abstract:
This thesis investigates the identification of general time-variant systems using Hilbert-Huang transform (HHT) and Bayesian inference. An HHT-based method is extended for general time variant systems. It is then combined with a Bayesian inference based method to obtain the distributions of system parameters. Another Bayesian inference based method is proposed using intrinsic mode functions to formulate the likelihood function. Numerical simulation results demonstrate the proposed methods.
| Zugehörige Institution(en) am KIT | Institut für Technische Mechanik (ITM) |
| Publikationstyp | Hochschulschrift |
| Publikationsjahr | 2017 |
| Sprache | Englisch |
| Identifikator | urn:nbn:de:swb:90-658120 KITopen-ID: 1000065812 |
| Verlag | Karlsruher Institut für Technologie (KIT) |
| Umfang | XXX, 201 S. |
| Art der Arbeit | Dissertation |
| Fakultät | Fakultät für Maschinenbau (MACH) |
| Institut | Institut für Technische Mechanik (ITM) |
| Prüfungsdatum | 08.02.2017 |
| Schlagwörter | Linear time-varying systems, weakly nonlinear time-varying systems, Hilbert-Huang transform, empirical mode decomposition, intrinsic mode function, Bayesian model updating and model class selection |
| Nachgewiesen in | OpenAlex |
| Referent/Betreuer | Proppe, C. |
