Embedded Files
A Parallel Wiener-Hammerstein system is obtained by connecting multiple Wiener-Hammerstein systems in parallel. Each parallel branch contains a static nonlinearity that is sandwiched in between two linear time-invariant (LTI) blocks. The presence of the two LTI blocks, and the parallel branches results in a problem that is harder to identify.
The provided data was part of a previously published Automatica paper available online at Sciencedirect or as an ArXiv preprint. The Parallel Wiener-Hammerstein system, the measurement setup, and the input signals used are detailed in Section 10 of the aforementioned paper. The provided Parallel Wiener-Hammerstein datasets are available for download here. This zip-file contains the multisine estimation data set, the multisine and an increasing-amplitude test data set. The data is available in the .csv and .mat file format.
Special thanks to Johan Pattyn for designing the parallel Wiener-Hammerstein system.
A two-branch Parallel Wiener-Hammerstein system: the red blocks represent linear time-invariant dynamics, while the blue blocks respresent a static nonlinearity.
Cite
Cite
Please refer to the Parallel Wiener-Hammerstein benchmark dataset as:
M. Schoukens, Parallel Wiener-Hammerstein Time Series, 4TU.ResearchData, 15-Sep-2020, doi: 10.4121/12950081.
M. Schoukens, A. Marconato, R. Pintelon, G. Vandersteen and Y. Rolain, Parametric identification of parallel Wiener–Hammerstein systems, Automatica, vol. 51, pp.111-122, 2015, doi: 10.1016/j.automatica.2014.10.105.
Benchmark Results
Benchmark Results
You can submit your own results through this form. Note that the reported results are curated, only complete submissions with meaningful contributions will be included. Candidate entries should make use of the Python dataloader functionalities and figure of merit calculation functions provided through this link.
Page updated
Google Sites
Report abuse