Robust sampling for MITL specifications

Georgios E. Fainekos, George J. Pappas

Research output: Chapter in Book/Report/Conference proceedingConference contribution

22 Scopus citations

Abstract

Real-time temporal logic reasoning about trajectories of physical systems necessitates models of time which are continuous. However, discrete time temporal logic reasoning is computationally more efficient than continuous time. Moreover, in a number of engineering applications only discrete time models are available for analysis. In this paper, we introduce a framework for testing MITL specifications on continuous time signals using only discrete time analysis. The motivating idea behind our approach is that if the dynamics of the signal fulfills certain conditions and the discrete time signal robustly satisfies the MITL specification, then the corresponding continuous time signal should also satisfy the same MITL specification.

Original languageEnglish (US)
Title of host publicationFormal Modeling and Analysis of Timed Systems - 5th International Conference, FORMATS 2007, Proceedings
PublisherSpringer Verlag
Pages147-162
Number of pages16
ISBN (Print)9783540754534
DOIs
StatePublished - 2007
Event5th International Conference on Formal Modelling and Analysis of Timed Systems, FORMATS 2007 - Salzburg, Austria
Duration: Oct 3 2007Oct 5 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4763 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other5th International Conference on Formal Modelling and Analysis of Timed Systems, FORMATS 2007
CountryAustria
CitySalzburg
Period10/3/0710/5/07

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    Fainekos, G. E., & Pappas, G. J. (2007). Robust sampling for MITL specifications. In Formal Modeling and Analysis of Timed Systems - 5th International Conference, FORMATS 2007, Proceedings (pp. 147-162). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4763 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-540-75454-1_12