TY - JOUR A1 - López C., Diana C. A1 - Barz, Tilman A1 - Körkel, Stefan A1 - Wozny, Günter T1 - Nonlinear ill-posed problem analysis in model-based parameter estimation and experimental design JF - Computers and Chemical Engineering N2 - Discrete ill-posed problems are often encountered in engineering applications. Still, their sound analysis is not yet common practice and difficulties arising in the determination of uncertain parameters are typically not assigned properly. This contribution provides a tutorial review on methods for identifiability analysis, regularization techniques and optimal experimental design. A guideline for the analysis and classification of nonlinear ill-posed problems to detect practical identifiability problems is given. Techniques for the regularization of experimental design problems resulting from ill-posed parameter estimations are discussed. Applications are presented for three different case studies of increasing complexity. Y1 - 2015 U6 - https://doi.org/10.1016/j.compchemeng.2015.03.002 VL - 77 SP - 24 EP - 42 PB - Elsevier CY - Amsterdam ER -