Nonlinear ill-posed problem analysis in model-based parameter estimation and experimental design

Diana C. López Cárdenas, Tilman Barz, Stefan Körkel, Günter Wozny

Publikation: Beitrag in FachzeitschriftArtikelBegutachtung

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.
OriginalspracheEnglisch
Seiten (von - bis)24-42
Seitenumfang19
FachzeitschriftComputers and Chemical Engineering
Volume77
DOIs
PublikationsstatusVeröffentlicht - 2015

Research Field

  • Ehemaliges Research Field - Energy

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