Abstract
When linear models cannot represent the system under test with sufficient accuracy, nonlinear models can be very useful. The model identified here on the benchmark system is a black-box nonlinear LFR (Linear Fractional Representation) model, consisting of MIMO linear dynamics and a SISO static nonlinear part. This model is capable of reproducing both nonlinear feed-forward and nonlinear feedback effects; it achieves a good accuracy-parsimony tradeoff. It will be identified from the best linear approximation estimated at two amplitude levels of the applied input force.
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Notes
- 1.
rms = Root Mean Square value.
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Acknowledgements
This work is sponsored by the Fund for Scientific Research (FWO-Vlaanderen), the Flemish Government (Methusalem Grant METH-1), the Belgian Program on Inter-university Poles of Attraction (IAP VII/19 - Dysco), and by the ERC advanced grant SNLSID, under contract 320378.
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© 2014 The Society for Experimental Mechanics, Inc.
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Vanbeylen, L., Van Mulders, A. (2014). Nonlinear Black-Box Identification of a Mechanical Benchmark System. In: Kerschen, G. (eds) Nonlinear Dynamics, Volume 2. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-04522-1_20
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DOI: https://doi.org/10.1007/978-3-319-04522-1_20
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