Experiments-Based Parameter Identification on the GPU for Cooperative Systems (Artikel)

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Experiments-Based Parameter Identification on the GPU for Cooperative Systems (Artikel)
Autor Ekaterina Auer, Andreas Rauh, Julia Kersten
In: Journal of Computational and Applied Mathematics
Ausgabe 371
ISBN/ISSN:
Erscheinungsjahr 2020
Jahrgang
Seitenzahl
Hyperlink https://doi.org/10.1016/j.cam.2019.112657
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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 identifying experimentally the parameters of the (reduced-order) temperature model for the distributed heating system. This is an important step towards working with uncertain models in the context of solid oxide fuel cells.