Challenges when Creating Variable-structure Models

Alexandra Mehlhase, Daniel Gomez Esperon, Thomas Karbe


Variable-structure models can switch their system of equations during a simulation, allowing for a change of level of detail or behavior. The need for this kind of models has been well-established, and there are simulation environments that can handle them. While most research papers on this topic focus on language and tool issues regarding variable-structure models, in this paper, we will shed some light on the pragmatics of actually creating such a model in a reusable way. During the construction of a variable-structure model, the modeler will face several challenges, such as the initialization of new modes during mode switches. We will collect and discuss the most important challenges and, if possible, provide rules of thumb on how to handle these challenges appropriately.


  1. Broman, D. (2010). Meta-Languages and Semantics for Equation-Based Modeling and Simulation. PhD thesis, Linköping University.
  2. Casella, F., Sielemann, M., and Savoldelli, L. (2011). Steady-state initialization of object-oriented thermofluid models for homotopy methods. In Proceedings of the 8th International Modelica Conference, pages 86-96.
  3. Clune, M., Mosterman, P., and Cassandras, C. (2006). Discrete event and hybrid system simulation with simevents. In Proceedings of the 8th International Workshop on Discrete Event Systems, pages 386-387.
  4. Dassault Systems (2015). Dassault Accessed: January 2015.
  5. Ehrich, A. (2012). Modellierung und Simulation eines Automatikgetriebes mit Strukturdynamik. Master's thesis, Technische Universität Berlin.
  6. Elmqvist, H., Cellier, F. E., and Otter, M. (1993). Objectoriented modeling of hybrid systems. In Proceedings of the European Simulation Symposium (ESS'93), Society of Computer Simulation, pages 31-41.
  7. GENSIM Project (2007). MOSILAB. Accessed: February 2015.
  8. Harel, D. (1987). Statecharts: A visual formalism for complex systems. Science of Computer Programming, 8(3):231-274.
  9. Heinzl, B. et al. (2012). Bcp - a benchmark for teaching structural dynamical systems. In Mathematical Modelling 7(1), pages 896-901.
  10. Mahr, B. (2008). Ein Modell des Modellseins - Ein Beitrag zur Aufklärung des Modellbegriffs. In Modelle. Ulrich Dirks, Eberhard Knobloch.
  11. Mehlhase, A. (2013). A Python framework to create and simulate models with variable structure in common simulation environments. Mathematical and Computer Modelling of Dynamical Systems, 20(6):566- 583.
  12. Mehlhase, A. et al. (2014). An example of beneficial use of variable-structure modeling to enhance an existing rocket model. In Proceedings of the 10th International Modelica Conference, pages 707-713. Linköping University Press.
  13. Mehlhase, A., Krüger, I., and Schmitz, G. (2012). Variable structure modeling for vehicle refrigeration applications. In Proceedings of the 9th International Modelica Conference, pages 927-934. Linköping University Electronic Press.
  14. Mosterman, P. J. and Biswas, G. (1997). Formal specifications for hybrid dynamical systems. In Proceedings of the 15th International Joint Conference Artificial Intelligence IJCAI-97, pages 568-573.
  15. Nilsson, H., Peterson, J., and Hudak, P. (2003). Functional hybrid modeling. In Proceedings of 5th Int. Workshop on Practical Aspects of Declarative Languages, volume 2562 of Lecture Notes in Computer Science, pages 376-390.
  16. Nytsch-Geusen, C. et al. (2005). Mosilab: Development of a modelica based generic simulation tool supporting model structural dynamics. In Proceedings of the 4th International Modelica Conference, pages 527-535.
  17. Pawletta, T., Lampe, B., Pawletta, S., and Drewelow, W. (2002). A devs-based approach for modeling and simulation of hybrid variable structure systems. In Modelling, Analysis, and Design of Hybrid Systems, Lecture Notes in Control and Information Sciences, volume 279, pages 107-129. Springer Berlin Heidelberg.
  18. Platzer, A. and Quesel, J. D. (2008). Keymaera: A hybrid theorem prover for hybrid systems (system description). In Proceedings of the 4th international joint conference on Automated Reasoning (IJCAR 7808), pages 171-178.
  19. Ptolemaeus, C., editor (2014). System Design, Modeling, and Simulation using Ptolemy II.
  20. The MathWorks Inc. (2013a). MATLAB, Simulink 2013b. Natick, Massachusetts, United States.
  21. The MathWorks Inc. (2013b). MATLAB, Stateflow 2013b. Natick, Massachusetts, United States.
  22. The Modelica Association (2012). Modelica - a unified object-oriented language for physical systems modeling - language specification version 3.3. Accessed: February 2015.
  23. Top, J. (1993). Conceptual Modelling of Physical Systems. PhD thesis, University of Twente.
  24. Zimmer, D. (2010). Equation-based modeling of variablestructure systems. PhD thesis, Eidgenössische Technische Hochschule ETH Zürich.

Paper Citation

in Harvard Style

Mehlhase A., Gomez Esperon D. and Karbe T. (2015). Challenges when Creating Variable-structure Models . In Proceedings of the 5th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH, ISBN 978-989-758-120-5, pages 101-110. DOI: 10.5220/0005521601010110

in Bibtex Style

author={Alexandra Mehlhase and Daniel Gomez Esperon and Thomas Karbe},
title={Challenges when Creating Variable-structure Models},
booktitle={Proceedings of the 5th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,},

in EndNote Style

JO - Proceedings of the 5th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,
TI - Challenges when Creating Variable-structure Models
SN - 978-989-758-120-5
AU - Mehlhase A.
AU - Gomez Esperon D.
AU - Karbe T.
PY - 2015
SP - 101
EP - 110
DO - 10.5220/0005521601010110