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arXiv · 2506.23744

On sample-based functional observability of linear systems

Isabelle Krauss·Victor G. Lopez·Matthias A. Müller
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Abstract

Sample-based observability characterizes the ability to reconstruct the internal state of a dynamical system by using limited output information, i.e., when measurements are only infrequently and/or irregularly available. In this work, we investigate the concept of functional observability, which refers to the ability to infer a function of the system state from the outputs, within a samplebased framework. Here, we give necessary and sufficient conditions for a system to be sample-based functionally observable, and formulate conditions on the sampling schemes such that these are satisfied. Furthermore, we provide a numerical example, where we demonstrate the applicability of the obtained results.

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Isabelle Krauss, Victor G. Lopez, Matthias A. Müller. 2025-06-30. On sample-based functional observability of linear systems. https://doi.org/10.1109/lcsys.2025.3582512

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