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Found 3 papers, 1 papers with code
Data-Driven Permissible Safe Control with Barrier Certificates
This paper introduces a method of identifying a maximal set of safe strategies from data for stochastic systems with unknown dynamics using barrier certificates.
Feasibility-Guided Safety-Aware Model Predictive Control for Jump Markov Linear Systems
In this paper, we present a framework that synthesizes maximally safe control policies for Jump Markov Linear Systems subject to stochastic mode switches.
Safety Guarantees for Neural Network Dynamic Systems via Stochastic Barrier Functions
A key step in our method is the employment of the recent convex approximation results for NNs to find piece-wise linear bounds, which allow the formulation of the barrier function synthesis problem as a sum-of-squares optimization program.
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