Learning piecewise-smooth dynamical systems
Discovering dynamical systems from trajectory data is a central problem in applied mathematics and engineering. Whilst recent advances in machine learning have led to strong progress in data-driven system identification, much less attention has been given to systems with discontinuous dynamics. These systems are nevertheless highly relevant in applications, including climate dynamics and mechanical systems with friction. In this work, we consider the problem of identifying piecewise-smooth dynamical systems directly from trajectory data. Compared with the smooth setting, this requires recovering the governing equations and detecting the switching hyperplanes that separate different dynami...
| Authors | Davide Murari, Erik Jansson, Chris Budd OBE et al. |
|---|---|
| Primary category | math.DS |
| Published | 20 August 2026 |
| Last updated at source | 20 August 2026 |
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