  In this paper, we propose a data-driven reachability analysis approach for
unknown system dynamics. 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 data-driven reachability
analysis approach from 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 Lipschitz
nonlinear systems. We provide theoretical guarantees in both cases. Numerical
examples show the potential and applicability of the introduced methods.
