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Model reduction of switched affine systems: a method based on balanced truncation and randomized optimization

Published:15 April 2014Publication History

ABSTRACT

This paper proposes an approach to build a reduced order model for a Switched Affine (SA) system. The main idea is to transform the SA system into an equivalent Switched Linear (SL) system with state reset, and then apply balanced truncation to each mode and redefine the reset maps so as to best reproduce the free evolution of the system output. A randomized method is proposed for order selection in the case when the input is stochastic and one is interested in reproducing the output of the original SA system over a finite time-horizon. The performance of the approach is shown on a benchmark example.

References

  1. A. Abate, S. Amin, M. Prandini, J. Lygeros, and S. Sastry. Computational approaches to reachability analysis of stochastic hybrid systems. In A. Bemporad, A. Bicchi, and G. Buttazzo, editors, Hybrid Systems: Computation and Control, volume 4416 of Lecture Notes in Computer Science, pages 4--17. Springer Berlin Heidelberg, apr 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. A. Abate, J.-P. Katoen, J. Lygeros, and M. Prandini. Approximate model checking of stochastic hybrid systems. European Journal of Control, special issue on Stochastic hybrid systems, 16(6):624--641, Dec. 20Google ScholarGoogle Scholar
  3. A. Abate and M. Prandini. Approximate abstractions of stochastic systems: a randomized method. In 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC), pages 4861--4866. IEEE, Dec 2011.Google ScholarGoogle ScholarCross RefCross Ref
  4. A. Antoulas. Approximation of large-scale dynamical systems, volume 6. Society for Industrial Mathematics, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. G. Calafiore and M. Campi. Uncertain convex programs: randomized solutions and confidence levels. Mathematical Programming, 102(1):25--46, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. M. Campi and S. Garatti. A sampling-and-discarding approach to chance-constrained optimization: Feasibility and optimality. Journal of Optimization Theory and Applications, 148(2):257--280, 2011.Google ScholarGoogle ScholarCross RefCross Ref
  7. M. C. Campi, S. Garatti, and M. Prandini. The scenario approach for systems and control design. Annual Reviews in Control, 33(2):149--157, 2009.Google ScholarGoogle ScholarCross RefCross Ref
  8. A. Fehnker and F. Ivancic. Benchmarks for hybrid systems verification. In In Hybrid Systems: Computation and Control (HSCC 2004), pages 326--341. Springer, 2004.Google ScholarGoogle ScholarCross RefCross Ref
  9. G. Frehse. Phaver: Algorithmic verification of hybrid systems past hytech. In Hybrid Systems: Computation and Control, pages 258--273. Springer, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. S. Garatti and M. Prandini. A simulation-based approach to the approximation of stochastic hybrid systems. In Analysis and Design of Hybrid Systems, pages 406--411, 2012.Google ScholarGoogle ScholarCross RefCross Ref
  11. A. Girard and C. Guernic. Zonotope/hyperplane intersection for hybrid systems reachability analysis. In Proceedings of the 11th international workshop on Hybrid Systems: Computation and Control, HSCC '08, pages 215--228, Berlin, Heidelberg, 2008. Springer-Verlag. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. A. Girard and G. Pappas. Approximation metrics for discrete and continuous systems. IEEE Trans. on Automatic Control, 52(5):782--798, 2007.Google ScholarGoogle ScholarCross RefCross Ref
  13. A. Girard, G. Pola, and P. Tabuada. Approximately bisimilar symbolic models for incrementally stable switched systems. IEEE Transactions on Automatic Control, 55(1):116--126, Jan 2010.Google ScholarGoogle ScholarCross RefCross Ref
  14. S. Gugercin and A. C. Antoulas. A survey of model reduction by balanced truncation and some new results. International Journal of Control, 77(8):748--766, 2004.Google ScholarGoogle ScholarCross RefCross Ref
  15. A. Julius and G. Pappas. Approximations of stochastic hybrid systems. IEEE Transactions on Automatic Control, 54(6):1193--1203, 2009.Google ScholarGoogle ScholarCross RefCross Ref
  16. A. B. Kurzhanski and P. Varaiya. Ellipsoidal techniques for hybrid dynamics: the reachability problem. In in New Directions and Applications in Control Theory, pages 193--205. Springer, 2005.Google ScholarGoogle ScholarCross RefCross Ref
  17. Y. Liu and B. D. Anderson. Singular perturbation approximation of balanced systems. International Journal of Control, 50(4):1379--1405, 1989.Google ScholarGoogle ScholarCross RefCross Ref
  18. J. Lunze and F. Lamnabhi-Lagarrigue, editors. Handbook of Hybrid Systems Control - Theory, Tools, Applications. Cambridge University Press, Cambridge, UK, 2009.Google ScholarGoogle Scholar
  19. E. Mazzi, A. Sangiovanni Vincentelli, A. Balluchi, and A. Bicchi. Hybrid system reduction. In 47th IEEE Conference on Decision and Control, pages 227--232. IEEE, Dec 2008.Google ScholarGoogle ScholarCross RefCross Ref
  20. I. Mitchell. Application of Level Set Methods to Control and Reachability Problems in Continuous and Hybrid Systems. PhD thesis, Ph.D. Dissertation. Dept. Scientific Computing and Computational Mathematics, Stanford Univ., CA, 2002.Google ScholarGoogle Scholar
  21. B. Moore. Principal component analysis in linear systems: Controllability, observability, and model reduction. IEEE Transactions on Automatic Control, 26(1):17--32, Feb 1981.Google ScholarGoogle ScholarCross RefCross Ref
  22. M. Petreczky and R. Vidal. Metrics and topology for nonlinear and hybrid systems. In Proceedings of the 10th International Conference on Hybrid Systems: Computation and Control, volume 4416 of Lecture Notes in Computer Sciences, pages 459--472, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. M. Petreczky, R. Wisniewski, and J. Leth. Theoretical analysis of balanced truncation for linear switched systems. In Analysis and Design of Hybrid Systems, pages 240--247, 2012.Google ScholarGoogle ScholarCross RefCross Ref
  24. M. Prandini and J. Hu. Stochastic reachability: Theoretical foundations and numerical approximation. In Stochastic hybrid systems, volume 24 of Control Engineering Series, pages 107--138. Taylor & Francis Group/CRC Press, 2006.Google ScholarGoogle Scholar
  25. A. Prékopa. Probabilistic programming. In A. Ruszczyński and A. Shapiro, editors, Stochastic Programming, volume 10 of handbooks in operations research and management science, London, UK, 2003. Elsevier.Google ScholarGoogle Scholar
  26. H. R. Shaker and R. Wisniewski. Model reduction of switched systems based on switching generalized gramians. International Journal of Innovative Computing, Information and Control, 8(7(B)):5025--5044, 2012.Google ScholarGoogle Scholar
  27. C. Tomlin, I. Mitchell, A. Bayen, and M. Oishi. Computational techniques for the verification of hybrid systems. Proceedings of the IEEE, 91(7):986--1001, 2003.Google ScholarGoogle ScholarCross RefCross Ref
  28. L. Zhang, B. Huang, and J. Lam. H∞ model reduction of Markovian jump linear systems. Systems & Control Letters, 50(2):103--118, 2003.Google ScholarGoogle ScholarCross RefCross Ref

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            cover image ACM Conferences
            HSCC '14: Proceedings of the 17th international conference on Hybrid systems: computation and control
            April 2014
            328 pages
            ISBN:9781450327329
            DOI:10.1145/2562059

            Copyright © 2014 ACM

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            Publication History

            • Published: 15 April 2014

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            HSCC '14 Paper Acceptance Rate29of69submissions,42%Overall Acceptance Rate153of373submissions,41%

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