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Main Authors: Ghanbarpour, Masoumeh, Sankaranarayanan, Sriram
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2508.20204
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author Ghanbarpour, Masoumeh
Sankaranarayanan, Sriram
author_facet Ghanbarpour, Masoumeh
Sankaranarayanan, Sriram
contents We study stochastic systems characterized by difference inclusions. Such stochastic differential inclusions are defined by set-valued maps involving the current state and stochastic input. For such systems, we investigate the problem of proving bounds on the worst-case probability of violating safety properties. Our approach uses the well-known concept of barrier functions from the study of stochastic control systems. However, barrier functions are hard to prove in the presence of stochastic inputs and adversarial choices due to the set-valued nature of the dynamics. In this paper, we show that under some assumptions on the set-valued map including upper semi-continuity and convexity combined with a concave barrier function vastly simplifies the proof of barrier conditions, allowing us to effectively substitute each random input in terms of its expectation. We prove key results based on the theory of set-valued maps and provide some interesting numerical examples. The ideas proposed here will contribute to the growing interest in problems of robust control and verification of stochastic systems in the presence of uncertain distributions and unmodeled dynamics.
format Preprint
id arxiv_https___arxiv_org_abs_2508_20204
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Characterization of Safety in Stochastic Difference Inclusions using Barrier Functions
Ghanbarpour, Masoumeh
Sankaranarayanan, Sriram
Optimization and Control
Systems and Control
We study stochastic systems characterized by difference inclusions. Such stochastic differential inclusions are defined by set-valued maps involving the current state and stochastic input. For such systems, we investigate the problem of proving bounds on the worst-case probability of violating safety properties. Our approach uses the well-known concept of barrier functions from the study of stochastic control systems. However, barrier functions are hard to prove in the presence of stochastic inputs and adversarial choices due to the set-valued nature of the dynamics. In this paper, we show that under some assumptions on the set-valued map including upper semi-continuity and convexity combined with a concave barrier function vastly simplifies the proof of barrier conditions, allowing us to effectively substitute each random input in terms of its expectation. We prove key results based on the theory of set-valued maps and provide some interesting numerical examples. The ideas proposed here will contribute to the growing interest in problems of robust control and verification of stochastic systems in the presence of uncertain distributions and unmodeled dynamics.
title Characterization of Safety in Stochastic Difference Inclusions using Barrier Functions
topic Optimization and Control
Systems and Control
url https://arxiv.org/abs/2508.20204