Abstract
Physical systems can be naturally modeled by combining continuous and discrete models. Such hybrid models may simplify the modeling task of complex system, as well as increase simulation performance. Moreover, modern simulation engines can often efficiently generate simulation traces, but how do we know that the simulation results are correct? If we detect an error, is the error in the model or in the simulation itself? This paper discusses the problem of simulation safety, with the focus on hybrid modeling and simulation. In particular, two key aspects are studied: safe zero-crossing detection and deterministic hybrid event handling. The problems and solutions are discussed and partially implemented in Modelica and Ptolemy II.
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Notes
- 1.
All examples in the paper are available here: http://www.modelyze.org/limbo.
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Acknowledgments
I would like to thank Edward for the really great collaboration we have had over the years. And, congratulations on your birthday! I would also like to thank Cludio Gomes, Oscar Eriksson, and the anonymous reviewers for many useful comments. Finally, I would like to acknowledge and thank Bernhard Rumpe for pointing out the connection between nondeterminism in models and underspecification.
This project is financially supported by the Swedish Foundation for Strategic Research (FFL15-0032).
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Broman, D. (2018). Hybrid Simulation Safety: Limbos and Zero Crossings. In: Lohstroh, M., Derler, P., Sirjani, M. (eds) Principles of Modeling. Lecture Notes in Computer Science(), vol 10760. Springer, Cham. https://doi.org/10.1007/978-3-319-95246-8_7
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