We present DT-Stark, an extension of the Stark tool aimed at the verification and evaluation of the effectiveness of digital twins, i.e., their ability to direct the physical counterparts. To this end, we introduce feedback in Stark, a special mechanism that allow us to model the communications, and their effects, between the digital and the physical (perturbed) twin in a concise, clean fashion. We can then exploit the features of Stark to compare the behaviour of the twins, to verify properties over them, and to measure effectiveness. We provide some examples of the use of our tool by applying it to the evaluation of the effectiveness of digital twins in two robotic scenarios.

Evaluating the Effectiveness of Digital Twins Through Statistical Model Checking with Feedback and Perturbations

Lanotte R.
;
Tini S.
2024-01-01

Abstract

We present DT-Stark, an extension of the Stark tool aimed at the verification and evaluation of the effectiveness of digital twins, i.e., their ability to direct the physical counterparts. To this end, we introduce feedback in Stark, a special mechanism that allow us to model the communications, and their effects, between the digital and the physical (perturbed) twin in a concise, clean fashion. We can then exploit the features of Stark to compare the behaviour of the twins, to verify properties over them, and to measure effectiveness. We provide some examples of the use of our tool by applying it to the evaluation of the effectiveness of digital twins in two robotic scenarios.
2024
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
9783031681493
9783031681509
29th International Conference on Formal Methods for Industrial Critical Systems, FMICS 2024
ita
2024
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11383/2179851
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