Conference article

An FMI-Based Tool for Robust Design of Dynamical Systems

Maria Henningsson
Modelon AB / Modelon Inc., Sweden

Johan Åkesson
Modelon AB / Modelon Inc., Sweden

Hubertus Tummescheit
Modelon AB / Modelon Inc., Sweden

Download articlehttp://dx.doi.org/10.3384/ecp1409635

Published in: Proceedings of the 10th International Modelica Conference; March 10-12; 2014; Lund; Sweden

Linköping Electronic Conference Proceedings 96:3, p. 35-42

Show more +

Published: 2014-03-10

ISBN: 978-91-7519-380-9

ISSN: 1650-3686 (print), 1650-3740 (online)

Abstract

Concepts from quality sciences; such as robust design; six-sigma; and design-of-experiments have had a large impact on product development in industry. These concepts are increasingly used in a model-based engineering context where data is gathered from simulation models rather than laboratory setups or prototypes.

This paper presents a framework to apply such ideas to analysis of dynamical systems. A set of tools that can be used for uncertainty analysis of dynamical Modelica models is presented. These tools are made available in the FMI Toolbox for MATLAB. The workflow and tools are demonstrated on a cooling loop design problem.

Keywords

Design-of-experiments; Robust design; Controls; Modelica; FMI

References

[1] D.W. Apley, J. Liu, andW. Chen. Understanding the effects of model uncertainty in robust design with computer experiments. Journal of Mechanical Design, 128:945–957, 2006. DOI: 10.1115/1.2204974

[2] R. A. Bates, R. S. Kenett, D. M. Steinberg, and H. P. Wynn. Achieving robust design from computer simulations. Quality Technology & Quantitative Management, 3(2):161–177, 2006.

[3] C. M. Bishop. Pattern Recognition and Machine Learning. Springer, 2006.

[4] D. Bouskela, A. Jardin, Z. Benjelloun-Touimi, P. Aronsson, and P. Fritzson. Modelling of uncertainties with Modelica. In Proceedings of the 8th International Modelica Conference, pages 673–685, 2011.

[5] C.M. Creveling, J.L. Slutsky, and D. Antis. Design for Six Sigma. Prentice Hall, Upper Saddle River, New Jersey, USA, 2003.

[6] B. Johansson and P. Krus. Probabilistic analysis and design optimization of Modelica models. In G. Schmitz, editor, Proceedings of the 4th International Modelica Conference, pages 247–254, 2005.

[7] P. N. Koch, R.-J. Yang, and L. Gu. Design for six sigma through robust optimization. Structural and Multidisciplinary Optimization, 26:235–248, 2004. DOI: 10.1007/s00158-003-0337-0

[8] K. Otto and K. Wood. Product Design. Prentice Hall, Upper Saddle River, New Jersey, USA, 2001.

[9] M. H. Salah, T. H. Mitchell, J. R. Wagner, and D. M. Dawson. A smart multiple-loop automotive cooling system—model, control , and experimental study. IEEE/ASME Transactions on Mechatronics, 15(1):117–124, 2010. DOI: 10.1109/TMECH.2009.2019723

[10] C. Zang, M. I. Friswell, and J. E. Mottershead. A review of robust optimal design and its application in dynamics. Computers & Structures, 83:315–326, 2005. DOI: 10.1016/j.compstruc.2004.10.007

Citations in Crossref