Controller Synthesis from Noisy-Input Noisy-Output Data
Systems and Control
2025-09-17 v1 Machine Learning
Systems and Control
Abstract
We consider the problem of synthesizing a dynamic output-feedback controller for a linear system, using solely input-output data corrupted by measurement noise. To handle input-output data, an auxiliary representation of the original system is introduced. By exploiting the structure of the auxiliary system, we design a controller that robustly stabilizes all possible systems consistent with data. Notably, we also provide a novel solution to extend the results to generic multi-input multi-output systems. The findings are illustrated by numerical examples.
Cite
@article{arxiv.2402.02588,
title = {Controller Synthesis from Noisy-Input Noisy-Output Data},
author = {Lidong Li and Andrea Bisoffi and Claudio De Persis and Nima Monshizadeh},
journal= {arXiv preprint arXiv:2402.02588},
year = {2025}
}