On continuous-time sparse identification of nonlinear polynomial systems

2025/09/22 by Mazen Alamir, Alamir, Mazen
Engineering · #Fault Detection and Control Systems #Control Systems and Identification #Adaptive Control of Nonlinear Systems

paper · pdf · doi:10.48550/arxiv.2509.17635

Abstract

This paper leverages recent advances in high derivatives reconstruction from noisy-time series and sparse multivariate polynomial identification in order to improve the process of parsimoniously identifying, from a small amount of data, unknown Single-Input/Single-Output nonlinear dynamics of relative degree up to 4. The methodology is illustrated on the Electronic Throttle Controlled automotive system.

Citations

• On reconstructing high derivatives of noisy time-series with confidence intervals
• PySINDy: A Python package for the Sparse Identification of Nonlinear Dynamics from Data

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