Reachability estimates of piecewise deterministic markov processes

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dc.contributor.author Tamba, Tua A.
dc.contributor.author Hu, Bin
dc.date.accessioned 2023-12-06T14:16:46Z
dc.date.available 2023-12-06T14:16:46Z
dc.date.issued 2022
dc.identifier.issn 2770-8373
dc.identifier.other maklhsc795
dc.identifier.uri http://hdl.handle.net/123456789/16657
dc.description Makalah dipresentasikan pada Proceedings of 2022 13th Asian Control Conference (ASCC); Jeju Island, Korea, May 4-7, 2022. p. 2327-2331 en_US
dc.description.abstract A piecewise deterministic Markov process (PDMP) is a stochastic process that is governed by random jumps at several time instances and evolves deterministically between those jumps. This paper presents an approximate solution for the reachability problem of such a PDMP. Given a PDMP that is defined on a bounded domain set and over a bounded time period, this paper examines the problem of estimating the probability that the PDMP’s sample paths will remain inside its domain set within the defined time period. The approach proposed in this paper is essentially constructed based on the solution of an initial boundary value problem (IBVP) of the considered PDMP. By imposing certain inequalities on the functions which consists in the solution of such an IBVP, this paper characterizes both under and over approximations of the probability that the PDMP’s sample paths will remain within its bounded domain. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject STOCHASTIC HYBRID SYSTEMS en_US
dc.subject PDMP en_US
dc.subject REACHABILITY en_US
dc.subject IBVP en_US
dc.subject FUNCTION INEQUALITY en_US
dc.title Reachability estimates of piecewise deterministic markov processes en_US
dc.type Conference Papers en_US


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