Marking Data-Informativity and Data-Driven Supervisory Control of Discrete-Event Systems
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arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| _version_ | 1866912946126323712 |
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| author | Liu, Yingying Fuchiwaki, Kuma Cai, Kai |
| author_facet | Liu, Yingying Fuchiwaki, Kuma Cai, Kai |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_05508 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Marking Data-Informativity and Data-Driven Supervisory Control of Discrete-Event Systems Liu, Yingying Fuchiwaki, Kuma Cai, Kai Formal Languages and Automata Theory Optimization and Control 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. |
| title | Marking Data-Informativity and Data-Driven Supervisory Control of Discrete-Event Systems |
| topic | Formal Languages and Automata Theory Optimization and Control |
| url | https://arxiv.org/abs/2603.05508 |