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Study about decomposition and integration of continuous systems in discrete environment

Thomas Paris 1, 2, * Alexandre Tan 1 Vincent Chevrier 3, 2 Laurent Ciarletta 1, 2
* Corresponding author
1 MADYNES - Management of dynamic networks and services
Inria Nancy - Grand Est, LORIA - NSS - Department of Networks, Systems and Services
2 SIMBIOT - SIMulating and Building IOT
LORIA - NSS - Department of Networks, Systems and Services
Abstract : A complex system is one composed of many interacting heterogeneous entities. This kind of system can be dealt with multi-modeling and co-simulation but individual models may also be heterogeneous (continuous , discrete, event-based...). To manage this complexity , we use MECSYCO (Multi-agent Environment for Complex-SYstem CO-simulation) a DEVS compliant environment for co-simulation. MECSYCO handles heterogeneity issues, but the number of models which may interact during a co-simulation of a complex system raises also performance issues. So it's important to develop performance measurement tools to study MECSYCO's co-simulation performances. In this article we present modular performance measurement tools for MECSYCO. We test these tools on our " Multi-Room Heating " model, a scalable continuous system, to assert the tradeoff between accuracy and computational time when integrating continuous system in a discrete modeling environment. Then we study the impact of decomposing a continuous system contained in one FMU into several FMUs which interact. We verify the validity of our tools and we show that, under some conditions, a large model that cannot be solved on one block, can be decomposed into smaller ones, solved and simulated in a co-simulation on MECSYCO without significant loss of accuracy.
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Submitted on : Wednesday, May 25, 2016 - 2:05:06 PM
Last modification on : Wednesday, November 3, 2021 - 7:08:55 AM
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  • HAL Id : hal-01256969, version 2


Thomas Paris, Alexandre Tan, Vincent Chevrier, Laurent Ciarletta. Study about decomposition and integration of continuous systems in discrete environment. Annual Simulation Symposium (ANSS), Apr 2016, Pasadena, United States. ⟨hal-01256969v2⟩



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