Hybrid Co-simulation of FMUs using DEV&DESS in MECSYCO - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Reports (Research Report) Year : 2016

Hybrid Co-simulation of FMUs using DEV&DESS in MECSYCO


Co-simulation is a key tool in the design and operation of a growing number of complex cyber-systems. But efficiently yet accurately combining continuous time components (such as FMUs) with event-based ones can be challenging, both from a modeling perspective and an operational, tools-oriented one. We propose a platform to tackle this problem building up on MECSYCO, a MAS-based DEVS wrapping platform dedicated to co-simulation. Relying on the ability of DEVS to integrate the DEV&DESS formalism-which offers a sound framework for describing hybrid models-we propose a DEV&DESS wrapper for FMU (i.e. continuous components implementing the FMI 2.0 standard). This wrapper encapsulates a version of the DEV&DESS simulation algorithm for FMU components which is notably composed of: (1) a forecast strategy which searches for the next state-event; (2) a bisectional algorithm to approach the location of the state-change in an FMU. Our solution is implemented using Java and JavaFMI to control the FMU. Our sample case is the co-simulation of a barrel-filler factory implemented in different FMUs and event-based models. Compared to related works, our proposal is functional, generic, yet evolutionary, and benefits from the strong foundations of DEV&DESS.
Fichier principal
Vignette du fichier
Hybrid_Cosimulation_of_FMU_using_DEVDESS_in_MECSYCO.pdf (365.63 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-01256738 , version 1 (15-01-2016)


  • HAL Id : hal-01256738 , version 1


Benjamin Camus, Virginie Galtier, Mathieu Caujolle, Vincent Chevrier, Julien Vaubourg, et al.. Hybrid Co-simulation of FMUs using DEV&DESS in MECSYCO. [Research Report] Université de Lorraine, CNRS, Inria, LORIA, UMR 7503; CentraleSupélec UMI GT-CNRS 2958 Université Paris-Saclay; EDF - R&D MIRE/R44. 2016. ⟨hal-01256738⟩
818 View
421 Download


Gmail Facebook X LinkedIn More