Abstract
Discrete ill-posed problems are often encountered in engineering applications. Still, their sound analysisis not yet common practice and difficulties arising in the determination of uncertain parameters are typ-ically not assigned properly. This contribution provides a tutorial review on methods for identifiabilityanalysis, regularization techniques and optimal experimental design. A guideline for the analysis and clas-sification of nonlinear ill-posed problems to detect practical identifiability problems is given. Techniquesfor the regularization of experimental design problems resulting from ill-posed parameter estimationsare discussed. Applications are presented for three different case studies of increasing complexity.
Originalsprache | Englisch |
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Seiten (von - bis) | 24-42 |
Seitenumfang | 19 |
Fachzeitschrift | Computers and Chemical Engineering |
Volume | 77 |
DOIs | |
Publikationsstatus | Veröffentlicht - 2015 |
Research Field
- Ehemaliges Research Field - Energy