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Data-Driven Abstraction of Monotone Systems
Anas Makdesi, Antoine Girard, Laurent Fribourg

Data-Driven Abstraction of Monotone Systems

Science & Mathematics Published 2021 Verification Pending

Overview & Synopsis

In this paper, we introduce an approach for the data-driven abstraction of monotone dynamical systems. First, we introduce a set-valued simulating map, which over-approximates the dynamics of an unknown monotone system, using only a set of transitions generated by it. We establish the minimality of the introduced simulating map. Then, we show that the system, with this map as its transition relation, is equivalent (in the sense of alternating bisimulation) to a finite-state system. This equivalence enables the use of well-established symbolic control techniques to synthesize controllers. We show the effectiveness of the approach on a safety controller synthesis problem.

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Document Information

Document Title Data-Driven Abstraction of Monotone Systems
Author / Organization Anas Makdesi, Antoine Girard, Laurent Fribourg
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2021
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-2631
Original Source Link Visit Source Page on hal.science »