Experiments-Based Parameter Identification on the GPU for Cooperative SOFC Temperature Models (Vortrag)

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Experiments-Based Parameter Identification on the GPU for Cooperative SOFC Temperature Models (Vortrag)
Autor Ekaterina Auer, Andreas Rauh, Julia Kersten
Tagung/Veranstaltung SCAN 2018
Ort Tokyo, japan
vom 10. September 2018 bis 15. September 2018
Review peer
Titel Proceedings
Autor Proceedings
Verlag
Erscheinungsjahr 2018

In this paper, we describe how to enhance experimental parameter identification for cooperative systems using the GPU. This kind of identification is necessary, for example, in the area of developing robust controllers and observers based on available measurement data. First, we point out which parts of the general, global optimization based parameter identification procedure can be parallelized and compare it to the experiments-based technique. After that, we illustrate the principle and its implementation with the help of a close-to-life textbook example. Finally, we demonstrate how the GPU-based experimental parameter identification works for a non-linear problem of identifying experimentally the parameters of the temperature model for the (reduced) distributed heating system. This is an important step towards working with uncertain models in the context of solid oxide fuel cells.