Loading...
Approximated stability analysis of bi-modal hybrid co-simulation scenarios
Gomes, C Karalis, P Vangheluwe, H
Gomes, C
Karalis, P
Vangheluwe, H
Editors
Other contributors
Affiliation
Epub Date
Issue Date
2018-02-02
Submitted date
Alternative
Abstract
Co-simulation is a technique to orchestrate multiple simulators in order to approximate the behavior of a coupled system as a whole. Simulators execute in a lockstep fashion, each exchanging inputs and output data points with the other simulators at pre-accorded times. In the context of systems with a physical and a cyber part, the communication frequency with which the simulators of each part communicate can have a negative impact in the accuracy of the global simulation results. In fact, the computed behavior can be qualitatively different, compared to the actual behavior of the original system, laying waste to potentially many hours of computation. It is therefore important to develop methods that answer whether a given communication frequency guarantees trustworthy co-simulation results. In this paper, we take a small step in that direction. We develop a technique to approximate the lowest frequency for which a particular set of simulation tools can exchange values in a co-simulation and obtain results that can be trusted.
Citation
Gomes C., Karalis P., Navarro-López E.M., Vangheluwe H. (2018) Approximated Stability Analysis of Bi-modal Hybrid Co-simulation Scenarios. In: Cerone A., Roveri M. (eds) Software Engineering and Formal Methods. SEFM 2017. Lecture Notes in Computer Science, vol 10729. Springer, Cham. https://doi.org/10.1007/978-3-319-74781-1_24
Publisher
Research Unit
PubMed ID
PubMed Central ID
Embedded videos
Additional Links
Type
Conference contribution
Language
en
Description
This is an accepted manuscript of an article published by Springer in: Cerone A., Roveri M. (eds) Software Engineering and Formal Methods. SEFM 2017. Lecture Notes in Computer Science, vol 10729, available online at: https://doi.org/10.1007/978-3-319-74781-1_24
The accepted version of the publication may differ from the final published version. For information on re-use, please refer to the publisher’s terms and conditions.
Series/Report no.
Lecture Notes in Computer Science, volume 10729
ISSN
0302-9743
EISSN
1611-3349
ISBN
9783319747804