Data-Driven Stabilization of Continuous-Time LTI Systems from Noisy Input-Output Data
Abstract
We present an approach to compute stabilizing controllers for continuous-time linear time-invariant systems directly from an input-output trajectory affected by process and measurement noise. The proposed output-feedback design combines (i) an observer of a non-minimal realization of the plant and (ii) a feedback law obtained from a linear matrix inequality (LMI) that depends solely on the available data. Under a suitable interval excitation condition and knowledge of a noise energy bound, the feasibility of the LMI is shown to be necessary and sufficient for stabilizing all non-minimal realizations consistent with the data. We further provide a condition for the feasibility of the LMI related to the signal-to-noise ratio, guidelines to compute the noise energy bound, and numerical simulations that illustrate the effectiveness of the approach.
Cite
@article{arxiv.2511.11417,
title = {Data-Driven Stabilization of Continuous-Time LTI Systems from Noisy Input-Output Data},
author = {Alessandro Bosso and Marco Borghesi and Andrea Iannelli and Bowen Yi and Giuseppe Notarstefano},
journal= {arXiv preprint arXiv:2511.11417},
year = {2025}
}