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arXiv · 2603.05508

Marking Data-Informativity and Data-Driven Supervisory Control of Discrete-Event Systems

Yingying Liu·Kuma Fuchiwaki·Kai Cai
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Abstract

In this paper we develop a data-driven approach for marking nonblocking supervisory control of discrete-event systems (DES). We consider a setup in which models of DES to be controlled are unknown, but a set of data concerning the behaviors of DES is available. We ask the question: Under what conditions of the available data set can a valid marking noblocking supervisor be designed for the unknown DES to satisfy a given specification? Answering this question, we identify and formalize a novel concept called marking data-informativity. Moreover, we design an algorithm for the verification of this concept. Next, if the data set fails to be marking informative, we propose two related new concepts of restricted marking data-informativity and marking informatizability. Finally, we develop an algorithm to compute the largest subset of control specification for which the data set is least restricted marking informative.

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Yingying Liu, Kuma Fuchiwaki, Kai Cai. 2026-01-14. Marking Data-Informativity and Data-Driven Supervisory Control of Discrete-Event Systems. https://arxiv.org/abs/2603.05508

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