Experiment design for grey box identification
| Autor: | Payman Sadegh, Jan Holst, H. Melgaard, Henrik Madsen |
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| Rok vydání: | 1995 |
| Předmět: |
Engineering
Grey box model business.industry Estimation theory Design of experiments Bayesian probability Extension (predicate logic) Identification (information) Control and Systems Engineering Signal Processing Probability distribution Artificial intelligence Electrical and Electronic Engineering business Algorithm Parametrization |
| Zdroj: | Technical University of Denmark Orbit |
| ISSN: | 1099-1115 0890-6327 |
| DOI: | 10.1002/acs.4480090604 |
| Popis: | Grey box models are characterized by their physical significance e.g. in parametrization and by the partial prior information that is available about e.g. the parameter values. These aspects of the grey box model affect the design of optimal excitations for identification and we study the extension of classical theory for experiment design to input design for identification of grey box models. Partial prior information is expressed as a probability distribution and is employed in the design of optimal excitations through optimization of Bayesian criteria. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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