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Stable Adaptive Co-simulation: A Switched Systems Approach

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IUTAM Symposium on Solver-Coupling and Co-Simulation

Part of the book series: IUTAM Bookseries ((IUTAMBOOK,volume 35))

Abstract

Co-simulation promotes the idea that domain specific simulation tools should cooperate in order to simulate the inter-domain interactions that are often observed in complex systems. To get trustworthy results, it is important that this technique preserves the stability properties of the original system. In this paper, we show how to preserve stability for adaptive co-simulation schemes, which offer fine grained control over the performance/accuracy of the co-simulation. To this end, we apply the joint spectral radius theory to certify that an adaptive co-simulation scheme is stable, and, if that is not possible, we use recent results in this field to create a trace of decisions that lead to instability. With this trace, it is possible to adjust the adaptive co-simulation in order to make it stable. Our approach is limited by the fact that computing the joint spectral radius is NP-Hard and undecidable in general. Nevertheless, we successfully applied our results to the co-simulation of a double mass-spring-damper system.

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Notes

  1. 1.

    Two well known standards for co-simulation—the Functional Mockup Interface Standard for co-simulation [10], and the High Level Architecture [1]—share this assumption.

  2. 2.

    http://msdl.cs.mcgill.ca/people/claudio/hybrid_cosim_analysis.

References

  1. IEEE Standard for Modeling and Simulation (M&S) High Level Architecture (HLA) - Federate Interface Specification. https://standards.ieee.org/findstds/standard/1516-2010.html (2010)

  2. Ahmadi, A.A., Jungers, R., Parrilo, P.A., Roozbehani, M.: Analysis of the joint spectral radius via lyapunov functions on path-complete graphs. In: Proceedings of the 14th International Conference on Hybrid Systems: Computation and Control - HSCC ’11, 13 pp. ACM Press, Chicago, IL, USA (2011). https://doi.org/10.1145/1967701.1967706

  3. Alvarez Cabrera, A.A., Woestenenk, K., Tomiyama, T.: An architecture model to support cooperative design for mechatronic products: a control design case. Mechatronics 21(3), 534–547 (2011). https://doi.org/10.1016/j.mechatronics.2011.01.009

    Article  Google Scholar 

  4. Arnold, M.: Stability of sequential modular time integration methods for coupled multibody system models. J. Comput. Nonlinear Dyn. 5(3), 9 (2010). https://doi.org/10.1115/1.4001389

    Article  Google Scholar 

  5. Arnold, M., Clauß, C., Schierz, T.: Error analysis and error estimates for co-simulation in FMI for model exchange and co-simulation v2.0. In: Schöps, S., Bartel, A., Günther, M., ter Maten, W.E.J., Müller, C.P. (eds.) Progress in Differential-Algebraic Equations, pp. 107–125. Springer Berlin Heidelberg, Berlin, Heidelberg (2014). https://doi.org/10.1007/978-3-662-44926-4_6

    Google Scholar 

  6. Bastian, J., Clauß, C., Wolf, S., Schneider, P.: Master for co-simulation using FMI. In: 8th International Modelica Conference, pp. 115–120. Linköping University Electronic Press, Linköpings universitet, Dresden, Germany (2011). https://doi.org/10.3384/ecp11063115

  7. Beltrame, G., Sciuto, D., Silvano, C.: Multi-accuracy power and performance transaction-level modeling. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 26(10), 1830–1842 (2007). https://doi.org/10.1109/TCAD.2007.895790

    Article  Google Scholar 

  8. Ben Khaled, A., Ben Gaid, M., Pernet, N., Simon, D.: Fast multi-core co-simulation of cyber-physical systems: application to internal combustion engines. Simul Model. Pract. Theory 47, 79–91 (2014). https://doi.org/10.1016/j.simpat.2014.05.002

    Article  Google Scholar 

  9. Blochwitz, T., Otter, M., Arnold, M., Bausch, C., Clauss, C., Elmqvist, H., Junghanns, A., Mauss, J., Monteiro, M., Neidhold, T., Neumerkel, D., Olsson, H., Peetz, J.V., Wolf, S.: The Functional mockup interface for tool independent exchange of simulation models. In: 8th International Modelica Conference, pp. 105–114. Linköping University Electronic Press; Linköpings universitet, Dresden, Germany (2011). https://doi.org/10.3384/ecp11063105

  10. Blockwitz, T., Otter, M., Akesson, J., Arnold, M., Clauss, C., Elmqvist, H., Friedrich, M., Junghanns, A., Mauss, J., Neumerkel, D., Olsson, H., Viel, A.: Functional mockup interface 2.0: the standard for tool independent exchange of simulation models. In: 9th International Modelica Conference, pp. 173–184. Linköping University Electronic Press, Munich, Germany (2012). https://doi.org/10.3384/ecp12076173

  11. Blondel, V.D., Tsitsiklis, J.N.: The boundedness of all products of a pair of matrices is undecidable. Syst. Control Lett. 41(2), 135–140 (2000). https://doi.org/10.1016/S0167-6911(00)00049-9

    Article  MathSciNet  MATH  Google Scholar 

  12. Busch, M.: Continuous approximation techniques for co-simulation methods: analysis of numerical stability and local error. ZAMM J. Appl. Math. Mech. 96(9), 1061–1081 (2016). https://doi.org/10.1002/zamm.201500196

    Article  MathSciNet  Google Scholar 

  13. Busch, M., Schweizer, B.: Numerical stability and accuracy of different co-simulation techniques: analytical investigations based on a 2-DOF test model. In: 1st Joint International Conference on Multibody System Dynamics, pp. 25–27 (2010)

    Google Scholar 

  14. Busch, M., Schweizer, B.: Stability of co-simulation methods using Hermite and Lagrange approximation techniques. In: ECCOMAS Thematic Conference on Multibody Dynamics, Brussels, Belgium, pp. 1–10 (2011)

    Google Scholar 

  15. Faure, C., Ben Gaid, M., Pernet, N., Fremovici, M., Font, G., Corde, G.: Methods for real-time simulation of cyber-physical systems: application to automotive domain. In: 2011 7th International Wireless Communications and Mobile Computing Conference, pp. 1105–1110. IEEE (2011). https://doi.org/10.1109/IWCMC.2011.5982695

  16. Friedrich, M.: Parallel co-simulation for mechatronic systems. Ph.D. thesis, Fakultät für Maschinenwesen (2011)

    Google Scholar 

  17. Gomes, C.: Foundations for continuous time hierarchical co-simulation. In: ACM Student Research Competition (ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems), p. to appear. ACM, New York, USA, Saint Malo, France (2016)

    Google Scholar 

  18. Gomes, C., Karalis, P., Navarro-López, E.M., Vangheluwe, H.: Approximated stability analysis of bi-modal hybrid co-simulation scenarios. In: 1st Workshop on Formal Co-Simulation of Cyber-Physical Systems, pp. 345–360. Springer, Cham, Trento, Italy (2017). https://doi.org/10.1007/978-3-319-74781-1_24

    Chapter  Google Scholar 

  19. Gomes, C., Thule, C., Broman, D., Larsen, P.G., Vangheluwe, H.: Co-simulation: state of the art. Technical report (2017). arXiv:1702.00686

  20. Gomes, C., Thule, C., Broman, D., Larsen, P.G., Vangheluwe, H.: Co-simulation: a Survey. ACM Comput. Surv. 51(3), Article 49 (2018). https://doi.org/10.1145/3179993

    Article  Google Scholar 

  21. Gripenberg, G.: Computing the joint spectral radius. Linear Algebra Appl. 234, 43–60 (1996). https://doi.org/10.1016/0024-3795(94)00082-4

    Article  MathSciNet  MATH  Google Scholar 

  22. Gu, B., Asada, H.H.: Co-simulation of algebraically coupled dynamic subsystems. In: American Control Conference, vol. 3, pp. 2273–2278. IEEE, Arlington, VA, USA (2001). https://doi.org/10.1109/ACC.2001.946089

  23. Guglielmi, N., Zennaro, M.: An algorithm for finding extremal polytope norms of matrix families. Linear Algebra Appl. 428(10), 2265–2282 (2008). https://doi.org/10.1016/j.laa.2007.07.009, http://linkinghub.elsevier.com/retrieve/pii/S0024379507003126

    Article  MathSciNet  Google Scholar 

  24. Hafner, I., Popper, N.: On the terminology and structuring of co-simulation methods. In: Proceedings of the 8th International Workshop on Equation-Based Object-Oriented Modeling Languages and Tools, pp. 67–76. ACM Press, New York, USA (2017). https://doi.org/10.1145/3158191.3158203

  25. Hines, K., Borriello, G.: Selective focus as a means of improving geographically distributed embedded system co-simulation. In: 8th IEEE International Workshop on Rapid System Prototyping, pp. 58–62 (1997). https://doi.org/10.1109/IWRSP.1997.618825

  26. Jungers, R.: The Joint Spectral Radius: Theory and Applications, vol. 385. Springer Science & Business Media, Berlin (2009)

    Google Scholar 

  27. Jungers, R.M., Cicone, A., Guglielmi, N.: Lifted polytope methods for computing the joint spectral radius. SIAM J. Matrix Anal. Appl. 35(2), 391–410 (2014). https://doi.org/10.1137/130907811

    Article  MathSciNet  MATH  Google Scholar 

  28. Kalmar-Nagy, T., Stanciulescu, I.: Can complex systems really be simulated? Appl. Math. Comput. 227, 199–211 (2014). https://doi.org/10.1016/j.amc.2013.11.037

    Article  MathSciNet  MATH  Google Scholar 

  29. Karner, M., Steger, C., Weiss, R., Armengaud, E.: Optimizing HW/SW co-simulation based on run-time model switching. In: 2009 Forum on Specification & Design Languages, FDL, pp. 1–6 (2009)

    Google Scholar 

  30. Karner, M., Armengaud, E., Steger, C., Weiss, R.: Holistic simulation of flexray networks by using run-time model switching. In: Proceedings of the Conference on Design, Automation and Test in Europe, DATE ’10, pp. 544–549. European Design and Automation Association, 3001 Leuven, Belgium (2010)

    Google Scholar 

  31. Kübler, R., Schiehlen, W.: Modular simulation in multibody system dynamics. Multibody Syst. Dyn. 4(2–3), 107–127 (2000). https://doi.org/10.1023/A:1009810318420

    Article  MATH  Google Scholar 

  32. Kübler, R., Schiehlen, W.: Two methods of simulator coupling. Math. Comput. Model. Dyn. Syst. 6(2), 93–113 (2000). https://doi.org/10.1076/1387-3954(200006)6:2;1-M;FT093

    Article  MATH  Google Scholar 

  33. Kundu, A., Chatterjee, D.: Stabilizing discrete-time switched linear systems. In: Hybrid Systems: Computation and Control, pp. 11–20. ACM Press, Berlin, Germany (2014). https://doi.org/10.1145/2562059.2562114, http://dl.acm.org/citation.cfm?doid=2562059.2562114

  34. Legat, B., Jungers, R.M., Parrilo, P.A.: Generating unstable trajectories for switched systems via dual sum-of-squares techniques. In: Proceedings of the 19th International Conference on Hybrid Systems: Computation and Control - HSCC ’16, pp. 51–60. ACM Press, New York, USA (2016). https://doi.org/10.1145/2883817.2883821

  35. Legat, B., Parrilo, P.A., Jungers, R.M.: Certifying unstability of switched systems using sum of squares programming. Technical report (2017). arXiv:1710.01814

  36. Lelarasmee, E., Ruehli, A.E., Sangiovanni-Vincentelli, A.L.: The waveform relaxation method for time-domain analysis of large scale integrated circuits. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 1, 131–145 (1982). https://doi.org/10.1109/TCAD.1982.1270004

    Article  Google Scholar 

  37. Lin, H., Antsaklis, P.J.: Stability and stabilizability of switched linear systems: a survey of recent results. IEEE Trans. Autom. Control 54(2), 308–322 (2009). https://doi.org/10.1109/TAC.2008.2012009, http://ieeexplore.ieee.org/document/4782010/

    Article  MathSciNet  Google Scholar 

  38. Maesumi, M.: An efficient lower bound for the generalized spectral radius of a set of matrices. Linear Algebra Appl. 240, 1–7 (1996). https://doi.org/10.1016/0024-3795(94)00171-5

    Article  MathSciNet  MATH  Google Scholar 

  39. Mosterman, P.J.: An overview of hybrid simulation phenomena and their support by simulation packages. In: Vaandrager, F.W., van Schuppen J.H. (eds.) Hybrid Systems: Computation and Control SE - 17. Lecture Notes in Computer Science, vol. 1569, pp. 165–177. Springer Berlin Heidelberg, Berg en Dal, The Netherlands (1999). https://doi.org/10.1007/3-540-48983-5_17

    Chapter  Google Scholar 

  40. Palensky, P., Van Der Meer, A.A., Lopez, C.D., Joseph, A., Pan, K.: Cosimulation of intelligent power systems: fundamentals, software architecture, numerics, and coupling. IEEE Ind. Electron. Mag. 11(1), 34–50 (2017). https://doi.org/10.1109/MIE.2016.2639825, http://ieeexplore.ieee.org/document/7883974/

    Article  Google Scholar 

  41. Parrilo, P.A., Jadbabaie, A.: Approximation of the joint spectral radius of a set of matrices using sum of squares. In: Hybrid Systems: Computation and Control, pp. 444–458. Springer, Berlin, Heidelberg, Pisa, Italy (2007). https://doi.org/10.1007/978-3-540-71493-4_35

  42. Parrilo, P.A., Jadbabaie, A.: Approximation of the joint spectral radius using sum of squares. Linear Algebra Appl. 428(10), 2385–2402 (2008). https://doi.org/10.1016/j.laa.2007.12.027, http://www.sciencedirect.com/science/article/pii/S0024379508000281, http://linkinghub.elsevier.com/retrieve/pii/S0024379508000281

    Article  MathSciNet  Google Scholar 

  43. Radetzki, M., Khaligh, R.S.: Accuracy-adaptive simulation of transaction level models. In: Proceedings of the Conference on Design, Automation and Test in Europe, DATE ’08, pp. 788–791. ACM, New York, USA (2008). https://doi.org/10.1145/1403375.1403566

  44. Rota, G.C., Strang, W.: A note on the joint spectral radius. In: Proceedings of the Netherlands Academy, vol. 22, pp. 379–381 (1960)

    Article  MathSciNet  Google Scholar 

  45. Schweizer, B., Li, P., Lu, D.: Explicit and implicit cosimulation methods: stability and convergence analysis for different solver coupling approaches. J. Comput. Nonlinear Dyn. 10(5), 051,007 (2015). https://doi.org/10.1115/1.4028503

    Article  Google Scholar 

  46. Schweizer, B., Li, P., Lu, D., Meyer, T.: Stabilized implicit co-simulation methods: solver coupling based on constitutive laws. Arch. Appl. Mech. 85(11), 1559–1594 (2015). https://doi.org/10.1007/s00419-015-0999-2

    Article  MATH  Google Scholar 

  47. Schweiger, G., Engel, G., Schoeggl, J., Hafner, I., Gomes, C., Nouidui, T.: Co-simulation – an empirical survey: applications, recent developments and future challenges. In: MATHMOD 2018 Extended Abstract Volume, pp. 125–126. ARGESIM Publisher Vienna, Vienna, Austria (2018). https://doi.org/10.11128/arep.55.a55286

  48. Stuart, A., Humphries, A.R.: Dynamical Systems and Numerical Analysis, vol. 2. Cambridge University Press, Cambridge (1998)

    MATH  Google Scholar 

  49. Sun, Z., Ge, S.: Analysis and synthesis of switched linear control systems. Automatica 41(2), 181–195 (2005). https://doi.org/10.1016/j.automatica.2004.09.015, http://linkinghub.elsevier.com/retrieve/pii/S0005109804002778

    Article  MathSciNet  Google Scholar 

  50. Tomiyama, T., D’Amelio, V., Urbanic, J., ElMaraghy, W.: Complexity of multi-disciplinary design. CIRP Ann. Manuf. Technol. 56(1), 185–188 (2007). https://doi.org/10.1016/j.cirp.2007.05.044

    Article  Google Scholar 

  51. Van der Auweraer, H., Anthonis, J., De Bruyne, S., Leuridan, J.: Virtual engineering at work: the challenges for designing mechatronic products. Eng. Comput. 29(3), 389–408 (2013). https://doi.org/10.1007/s00366-012-0286-6

    Article  Google Scholar 

  52. Wanner, G., Hairer, E.: Solving Ordinary Differential Equations I: Nonstiff Problems, vol. 1, Springer’s edn. Springer, Berlin (1991)

    Google Scholar 

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Gomes, C., Legat, B., Jungers, R.M., Vangheluwe, H. (2019). Stable Adaptive Co-simulation: A Switched Systems Approach. In: Schweizer, B. (eds) IUTAM Symposium on Solver-Coupling and Co-Simulation. IUTAM Bookseries, vol 35. Springer, Cham. https://doi.org/10.1007/978-3-030-14883-6_5

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