Data-driven input reconstruction and experimental validation
Systems and Control
2023-08-21 v1 Systems and Control
Abstract
This paper addresses a data-driven input reconstruction problem based on Willems' Fundamental Lemma in which unknown input estimators (UIEs) are constructed directly from historical I/O data. Given only output measurements, the inputs are estimated by the UIE, which is shown to asymptotically converge to the true input without knowing the initial conditions. Both open-loop and closed-loop UIEs are developed based on Lyapunov conditions and the Luenberger-observer-type feedback, whose convergence properties are studied. An experimental study is presented demonstrating the efficacy of the closed-loop UIE for estimating the occupancy of a building on the EPFL campus via measured carbon dioxide levels.
Cite
@article{arxiv.2203.02827,
title = {Data-driven input reconstruction and experimental validation},
author = {Jicheng Shi and Yingzhao Lian and Colin N. Jones},
journal= {arXiv preprint arXiv:2203.02827},
year = {2023}
}