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Lagrangian Reachtubes: The Next Generation

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dc.abstract.enWe introduce LRT-NG, a set of techniques and an associated toolset that computes a reachtube (an over-approximation of the set of reachable states over a given time horizon) of a nonlinear dynamical system. LRT-NG significantly advances the state-of-the-art Langrangian Reachability and its associated tool LRT. From a theoretical perspective, LRT-NG is superior to LRT in three ways. First, it uses for the first time an analytically computed metric for the propagated ball which is proven to minimize the ball's volume. We emphasize that the metric computation is the centerpiece of all bloating-based techniques. Secondly, it computes the next reachset as the intersection of two balls: one based on the Cartesian metric and the other on the new metric. While the two metrics were previously considered opposing approaches, their joint use considerably tightens the reachtubes. Thirdly, it avoids the "wrapping effect" associated with the validated integration of the center of the reachset, by optimally absorbing the interval approximation in the radius of the next ball. From a tool-development perspective, LRT-NG is superior to LRT in two ways. First, it is a standalone tool that no longer relies on CAPD. This required the implementation of the Lohner method and a Runge-Kutta time-propagation method. Secondly, it has an improved interface, allowing the input model and initial conditions to be provided as external input files. Our experiments on a comprehensive set of benchmarks, including two Neural ODEs, demonstrates LRT-NG's superior performance compared to LRT, CAPD, and Flow*.
dc.affiliationUniwersytet Warszawski
dc.conference.countryKorea Południowa
dc.conference.datefinish2020-12-18
dc.conference.datestart2020-12-14
dc.conference.placeJeju Island
dc.conference.seriesIEEE Conference on Decision and Control
dc.conference.seriesIEEE Conference on Decision and Control
dc.conference.seriesshortcutCDC
dc.conference.shortcutCDC 2020
dc.conference.weblinkhttps://cdc2020.ieeecss.org/
dc.contributor.authorGruenbacher, Sophie
dc.contributor.authorIslam, Md. Ariful
dc.contributor.authorLechner, Mathias
dc.contributor.authorGrosu, Radu
dc.contributor.authorSmolka, Scott A.
dc.contributor.authorCyranka, Jacek
dc.date.accessioned2024-01-25T04:58:56Z
dc.date.available2024-01-25T04:58:56Z
dc.date.issued2020
dc.description.financePublikacja bezkosztowa
dc.identifier.doi10.1109/CDC42340.2020.9304042
dc.identifier.urihttps://repozytorium.uw.edu.pl//handle/item/110829
dc.identifier.weblinkhttp://xplorestaging.ieee.org/ielx7/9303728/9303729/09304042.pdf?arnumber=9304042
dc.languageeng
dc.pbn.affiliationcomputer and information sciences
dc.relation.pages1556 - 1563
dc.rightsClosedAccess
dc.sciencecloudnosend
dc.subject.enMeasurement
dc.subject.enTools
dc.subject.enLight rail systems
dc.subject.enEllipsoids
dc.subject.enWrapping
dc.subject.enStrain
dc.subject.enProgramming
dc.titleLagrangian Reachtubes: The Next Generation
dc.typeJournalArticle
dspace.entity.typePublication