TY - JOUR A1 - Barz, Tilman A1 - López C., Diana C. A1 - Körkel, Stefan A1 - Walter, Sebastian F. T1 - Real-time adaptive input design for the determination of competitive adsorption isotherms in liquid chromatography JF - Computers and Chemical Engineering N2 - The adaptive input design (also called online redesign of experiments) for parameter estimation is very effective for the compensation of uncertainties in nonlinear processes. Moreover, it enables substantial savings in experimental effort and greater reliability in modeling. We present theoretical details and experimental results from the real-time adaptive optimal input design for parameter estimation. The case study considers separation of three benzoate by reverse phase liquid chromatography. Following a receding horizon scheme, adaptive D-optimal input designs are generated for a precise determination of competitive adsorption isotherm parameters. Moreover, numerical techniques for the regularization of arising ill-posed problems, e.g. due to scarce measurements, lack of prior information about parameters, low sensitivities and parameter correlations are discussed. The estimated parameter values are successfully validated by Frontal Analysis and the benefits of optimal input designs are highlighted when compared to various standard/heuristic input designs in terms of parameter accuracy and precision. Y1 - 2016 U6 - https://doi.org/10.1016/j.compchemeng.2016.07.009 VL - 94 SP - 104 EP - 116 PB - Elsevier ER - 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 -