{"title":"Formal safety verification of non-deterministic systems based on probabilistic reachability computation","authors":"Yuminghao Xiao, Tianbing Xia, Hongdong Wang","doi":"10.1016/j.sysconle.2024.106014","DOIUrl":null,"url":null,"abstract":"<div><div>In this paper, we develop a formal safety verification method based on analytic probabilistic reachability computation, which can estimate the probability of controlled non-deterministic systems entering unsafe states subject to disturbances. Specifically, we employ stochastic differential equations (SDEs) to describe the dynamics of the system and resort to a regularized indicator function to express the collision probability between the state trajectory of the system and unsafe states. We proceed to formulate this collision probability as the viscosity solution to a second-order variational-inequality and provide a rigorous proof for such a novel interpretation. Moreover, we discuss the ENO-Godunov scheme for solving the deduced variational-inequality, which obviates the need for Monte-Carlo simulations and the optimality condition along a complex boundary. The developed framework offers a structured approach to identify potential risks in safety critical systems and maintains a user-friendly implementation. Lastly, we demonstrate the above application in a safety verification problem related to maritime navigation.</div></div>","PeriodicalId":49450,"journal":{"name":"Systems & Control Letters","volume":"196 ","pages":"Article 106014"},"PeriodicalIF":2.1000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Systems & Control Letters","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167691124003025","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we develop a formal safety verification method based on analytic probabilistic reachability computation, which can estimate the probability of controlled non-deterministic systems entering unsafe states subject to disturbances. Specifically, we employ stochastic differential equations (SDEs) to describe the dynamics of the system and resort to a regularized indicator function to express the collision probability between the state trajectory of the system and unsafe states. We proceed to formulate this collision probability as the viscosity solution to a second-order variational-inequality and provide a rigorous proof for such a novel interpretation. Moreover, we discuss the ENO-Godunov scheme for solving the deduced variational-inequality, which obviates the need for Monte-Carlo simulations and the optimality condition along a complex boundary. The developed framework offers a structured approach to identify potential risks in safety critical systems and maintains a user-friendly implementation. Lastly, we demonstrate the above application in a safety verification problem related to maritime navigation.
期刊介绍:
Founded in 1981 by two of the pre-eminent control theorists, Roger Brockett and Jan Willems, Systems & Control Letters is one of the leading journals in the field of control theory. The aim of the journal is to allow dissemination of relatively concise but highly original contributions whose high initial quality enables a relatively rapid review process. All aspects of the fields of systems and control are covered, especially mathematically-oriented and theoretical papers that have a clear relevance to engineering, physical and biological sciences, and even economics. Application-oriented papers with sophisticated and rigorous mathematical elements are also welcome.