تقرير
Adaptive planning for risk-aware predictive digital twins
| العنوان: | Adaptive planning for risk-aware predictive digital twins |
|---|---|
| المؤلفون: | Tezzele, Marco, Carr, Steven, Topcu, Ufuk, Willcox, Karen E. |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science Mathematics |
| مصطلحات موضوعية: | Mathematics - Numerical Analysis |
| الوصف: | This work proposes a mathematical framework to increase the robustness to rare events of digital twins modelled with graphical models. We incorporate probabilistic model-checking and linear programming into a dynamic Bayesian network to enable the construction of risk-averse digital twins. By modeling with a random variable the probability of the asset to transition from one state to another, we define a parametric Markov decision process. By solving this Markov decision process, we compute a policy that defines state-dependent optimal actions to take. To account for rare events connected to failures we leverage risk measures associated with the distribution of the random variables describing the transition probabilities. We refine the optimal policy at every time step resulting in a better trade off between operational costs and performances. We showcase the capabilities of the proposed framework with a structural digital twin of an unmanned aerial vehicle and its adaptive mission replanning. |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2407.20490 |
| رقم الأكسشن: | edsarx.2407.20490 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |