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arXiv · 2403.00578

SINDy vs Hard Nonlinearities and Hidden Dynamics: a Benchmarking Study

Aurelio Raffa Ugolini·Valentina Breschi·Andrea Manzoni·Mara Tanelli
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Abstract

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.

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BibTeXRIS

Aurelio Raffa Ugolini, Valentina Breschi, Andrea Manzoni, Mara Tanelli. 2024-03-01. SINDy vs Hard Nonlinearities and Hidden Dynamics: a Benchmarking Study. https://arxiv.org/abs/2403.00578

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