LoginRegistration
For instance: The List of VAK
About consortium subscription Contacts
(812) 4095364 Non-commercial partnership
St. Petersburg
university
consortium

Articles

"Humanities and Science University Journal" №10 (Physical and mathematical, biological and technical science), 2014.

Realisation Preserving Modelling in Modelica

B. Zupancic
Price: 50 руб.
 Realisation-preserving modelling is a modelling when a computer aided approach is used with the basic aim to keep the physical structure of a real system or its topology as much as possible in the model and can be effi ciently supported by new object-oriented and multi-domain tools based on the Modelica language. The important advantages of such tools in comparison with traditional block oriented modelling
approaches are described. The paper also describes an education (laboratory helicopter) and an industrial application project (thermal and radiation fl ows in buildings) in the Modelica environment and some experience obtained from these projects and from a more general usage of the Modelica environment. However, models in Modelica become very complex, which also causes numerical problems that are diffi cult to diagnose. So, simplifi cation and/or reduction wherever possible are
important. Therefore, we propose some model reduction solutions for both modelling levels- for the equation and diagram layer.
Keywords: realisation-preserving modelling, object oriented modelling, acausal
modelling, physical modelling, multi-domain modelling, model reduction.
REFERENCES
1. Borutsky, W. Bond graph methodology, development and analysis of multidisciplinary dynamic system models. 2010, Germany: Springer.
2. Cellier, F.E. Continuous system modeling. 1991, USA: Springer Verlag.
3. Dymola, Multi-engineering modelling and simulation. 2010, Users manual, Ver. 7.3.
4. Ersal, T. Realization-preserving simpli fi cation and reduction of dynamic system
models at the graph level (PhD Thesis). 2007, University Of Michigan.
5. Fritzson, P. Principles of object oriented modelling and simulation with Modelica
2.1. 2004, USA: IEEE Press, John Wiley&Sons Inc.
6. Humusoft, CE 150 Helicopter model. 2002, User’s manual, Prague: Humusoft.
7. Karer, G., & Zupančič, B. Modelling and identi fi cation of a laboratory helicopter.
In Proceedings of the 5th MATHMOD conference (Vol. 2), 2006, Vienna.
8. Lee, K., & Braun, J.E. Model-based demand-limiting control of building thermal
mass. Building and Environment, 2008, Vol. 43, 1633−1646.
9. Logar, V., Kristl, Ž., & Škrjanc, I. Using a fuzzy black-box model to estimate the
indoor illuminance in buildings. Energy and Buildings, 2014, Vol. 70, 343−351.
10. Louca, L.S. An energy-based model reduction methodology for automated
modeling (PhD Thesis). 1998, University of Michigan.
11. Modelica association. Modelica speci fi cation, v. 3.1. 2009, Retrieved December
20, 2014, from https://www.modelica.org/documents/ModelicaSpec31.pdf/at_download/fi le
12. Sheehan, B.N. TICER: Realizable reduction of extracted RC circuits. In IEEE/
ACM International Conference on Computer-Aided Design, Digest of Technical Papers,
1999, pp. 200−203.13.
13. Sodja, A. Object-oriented modelling and simulation analysis of the automatically
translated models (PhD Thesis). 2012, University of Ljubljana, Faculty of El. Eng.
14. Sodja, A., & Zupančič, B. Modelling thermal processes in buildings using an
object-oriented approach and Modelica. Simulation Modelling Practice and Theory,
2009, Vol. 17, Iss. 6, 1143−1159.
15. Sodja, A., & Zupančič, B. On using model approximation techniques for better
understanding of models implemented in Modelica. In Proceedings of 8th International
Modelica Conference, Dresden, Germany, 2011, pp. 697−703.
16. Sodja, A., & Zupančič, B. Realisation-preserving model reduction of models
in Modelica. In Proceedings of 7th MATHMOD Conference, 2012, Vienna, Austria,
pp. 322−328.
17. Sodja, A., & Zupančič, B. Some aspects of thermal and radiation fl ows modelling in buildings using Modelica. In Proceedings of 10th International Conference on
Computer Modelling and Simulation UKSIM/EUROSIM (pp. 637−642), 2008, Cambridge, UK.
18. Sommer, R, Halfmann, T, & Broz, J. Automated behavioral modeling and analytical model-order reduction by application of symbolic circuit analysis for multi-physical
systems. Simulation Modelling Practice and Theory, 2008, Vol. 16, 1024−1039.
19. Škrjanc, I., Zupančič, B., Furlan, B., & Krainer, A. Theoretical and experimental
fuzzy modelling of building thermal dynamic response. Building and Environment,
2001, Vol. 36, No. 9, 1023−1038.
20. Tomažič, S., Logar, V., Kristl, Ž., Krainer, A., Škrjanc, I., & Košir, M. Indoorenvironment simulator for control design purposes. Building and environment, 2013, Vol. 70, 60−72.
21. Ugryumova, M.V. Applications of model order reduction for IC modeling (PhD
Thesis). 2011, Eindhoven University of Technology.
22. Wilson, B.H., & Stein, J.L. An algorithm for obtaining proper models of distributed and discrete systems. ASME Journal of Dynamic Systems, Measurement and
Control, 1955, Vol. 117(4), 534−540.
23. Ye, Y., & Youcef, Y.K. Model reduction in the physical domain. In Proceedings
of the American Control Conference, 1999, San Diego, CA, USA, pp. 4486−4490.
24. Zupančič, B., & Sodja, A. Object oriented modelling of variable envelope properties in buildings. WSEAS transactions on systems and control, 2008, Vol. 3, No. 12,
1046−1056.
Price: 50 рублей
To order