Wiener-Hammerstein benchmark with process noise
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
Datacite citation style:
Schoukens, Maarten; Noël, Jean-Philippe (2020): Wiener-Hammerstein benchmark with process noise. Version 2. 4TU.ResearchData. dataset. https://doi.org/10.4121/12952124.v2Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
version 2 - 2020-09-22 (latest)version 1 - 2020-09-21
licenceCC BY-SA 4.0
The Wiener-Hammerstein system structure is a well-known block-oriented structure. It contains a static nonlinearity that is sandwiched in between two linear time-invariant (LTI) blocks. The presence of the two LTI blocks results in a problem that is harder to identify. The LTI blocks are realized as active filters while the static nonlinearity is implemented as a diode-resistor electronic circuit.
The Wiener-Hammerstein system proposed here as a benchmark contains dominant process noise. The process noise enters the system before the static nonlinearity. Two much less significant noise sources are present in the measurement channels of the input and output.
All the provided files, data and information on the Wiener-Hammerstein system are available for download here together with an in-depth description of the measured input-output time series. This zip-file contains a detailed system description, an example estimation data set, the test data sets, the datasets measured during the past measurement campaign(s), pictures of the measurement setup, and an indicative electrical circuit schematic of the system. It is possible that the actual implemented Wiener-Hammerstein system deviates at some points (resistor values, opamp type) from the electrical circuit provided here. The data is available in the .csv and .mat file format.
- 2020-09-21 first online
- 2020-09-22 published, posted
associated peer-reviewed publicationThree Benchmarks Addressing Open Challenges in Nonlinear System Identification
organizationsEindhoven University of Technology, Department of Electrical Engineering, Control System group