SINDy-PI: a robust algorithm for parallel implicit sparse identification of nonlinear dynamics | Proceedings A | The Royal Society
Kadierdan Kaheman, J. Nathan Kutz, Steven L. Brunton; SINDy-PI: a robust algorithm for parallel implicit sparse identification of nonlinear dynamics. Proc. R. Soc. A 1 October 2020; 476 (2242): 20200279. https://doi.org/10.1098/rspa.2020.0279 Download citation file: Accurately modelling the nonlinear dynamics of a system from measurement data is a challenging yet vital topic. The sparse identification of nonlinear dynamics (SINDy) algorithm is one approach to discover dynamical systems models from data. Although extensions have been developed to identify implicit dynamics, or dynamics described by rational functions, these extensions are extremely sensitive to noise. In this work, we develop SINDy-PI (parallel, implicit), a robust variant of the SINDy algorithm to identify implicit dynamics and rational nonlinearities. The SINDy-PI framework includes multiple optimization algorithms and a principled approach to model selection. We demonstrate the ability of this algorithm to learn impl