Data-Driven Reachability Analysis Using Matrix Zonotopes
Abstract
In this paper, we propose a data-driven reachability analysis approach for an unknown control system. Reachability analysis is an essential tool for guaranteeing safety properties. However, most current reachability analysis heavily relies on the existence of a suitable system model, which is often not directly available in practice. We instead propose a reachability analysis approach based on noisy data. More specifically, we first provide an algorithm for over-approximating the reachable set of a linear time-invariant system using matrix zonotopes. Then we introduce an extension for nonlinear systems. We provide theoretical guarantees in both cases. Numerical examples show the potential and applicability of the introduced methods.
Cite
Text
Alanwar et al. "Data-Driven Reachability Analysis Using Matrix Zonotopes." Proceedings of the 3rd Conference on Learning for Dynamics and Control, 2021.Markdown
[Alanwar et al. "Data-Driven Reachability Analysis Using Matrix Zonotopes." Proceedings of the 3rd Conference on Learning for Dynamics and Control, 2021.](https://mlanthology.org/l4dc/2021/alanwar2021l4dc-datadriven/)BibTeX
@inproceedings{alanwar2021l4dc-datadriven,
title = {{Data-Driven Reachability Analysis Using Matrix Zonotopes}},
author = {Alanwar, Amr and Koch, Anne and Allgöwer, Frank and Johansson, Karl Henrik},
booktitle = {Proceedings of the 3rd Conference on Learning for Dynamics and Control},
year = {2021},
pages = {163-175},
volume = {144},
url = {https://mlanthology.org/l4dc/2021/alanwar2021l4dc-datadriven/}
}