SINDy vs Hard Nonlinearities and Hidden Dynamics: a Benchmarking Study
<|reference_start|>SINDy vs Hard Nonlinearities and Hidden Dynamics: a Benchmarking Study: In this work we analyze the effectiveness of the Sparse Identification of Nonlinear Dynamics (SINDy) technique on three benchmark datasets for nonlinear identification, to provide a better understanding of its suitability when tackling real dynamical systems. While SINDy can be an appealing strategy for pursuing physics-based learning, our analysis highlights difficulties in dealing with unobserved states and non-smooth dynamics. Due to the ubiquity of these features in real systems in general, and control applications in particular, we complement our analysis with hands-on approaches to tackle these issues in order to exploit SINDy also in these challenging contexts.<|reference_end|>
@article{ugolini2024sindy,
    title={SINDy vs Hard Nonlinearities and Hidden Dynamics: a Benchmarking Study},
    author={Aurelio Raffa Ugolini and Valentina Breschi and Andrea Manzoni and
  Mara Tanelli},
    journal={arXiv preprint arXiv:2403.00578},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.00578},
    primaryClass={eess.SY cs.LG cs.SY}
}