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An algorithmic approach to global asymptotic stability verification of hybrid systems

Published:01 October 2016Publication History

ABSTRACT

In this paper, we present an algorithmic approach to global asymptotic stability (GAS) verification of hybrid systems. Our broad approach consists of reducing the GAS verification to the verification of a region stability (RS) analysis problem and an asymptotic stability (AS) analysis problem. We use a recently developed quantitative predicate abstraction technique for AS analysis and extract from it a stability zone with respect to which we perform RS analysis. We present a new algorithm for RS analysis based on abstractions. While we develop the theory for polyhedral hybrid systems, our broad approach of decomposing GAS analysis to RS and AS analysis can be applied to more general class of systems including linear hybrid systems. As a proof of concept, we apply the GAS verification algorithm to a linear hybrid system model of a cruise control for an automatic gearbox, and provide a semi-automated proof of GAS.

References

  1. Rajeev Alur, Costas Courcoubetis, Thomas A. Henzinger, and Pei hsin Ho. Hybrid automata: An algorithmic approach to the specification and verification of hybrid systems. In Hybrid Systems, pages 209--229, 1992. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. E. Asarin, T. Dang, and A. Girard. Hybridization methods for the analysis of nonlinear systems. Acta Informatica, 43(7):451--476, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. T. Dang, O. Maler, and R. Testylier. Accurate hybridization of nonlinear systems. In Proceedings of the International Conference on Hybrid Systems: Computation and Control, pages 11--20, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Parasara Sridhar Duggirala and Sayan Mitra. Abstraction refinement for stability. In Proceedings of the International Conference on Cyber-Physical Systems, pages 22--31, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Parasara Sridhar Duggirala and Sayan Mitra. Lyapunov abstractions for inevitability of hybrid systems. In Proceedings of the International Conference on Hybrid Systems: Computation and Control, pages 115--124, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. R. Goebel, R.G. Sanfelice, and A.R. Teel. Hybrid dynamical systems. IEEE Control Systems Magazine, 29:28--93, 2009.Google ScholarGoogle ScholarCross RefCross Ref
  7. James Kapinski, Jyotirmoy V. Deshmukh, Sriram Sankaranarayanan, and Nikos Arechiga. Simulation-guided lyapunov analysis for hybrid dynamical systems. In Proceedings of the International Conference on Hybrid Systems: Computation and Control, pages 133--142, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. H. K. Khalil. Nonlinear Systems. Prentice-Hall, Upper Saddle River, NJ, 1996.Google ScholarGoogle Scholar
  9. D. Liberzon. Switching in Systems and Control. Boston : Birkhäuser, 2003.Google ScholarGoogle Scholar
  10. Hai Lin and Panos J. Antsaklis. Stability and stabilizability of switched linear systems: A survey of recent results. IEEE Transactions on Automatic Control, 54(2):308--322, 2009.Google ScholarGoogle ScholarCross RefCross Ref
  11. Paolo Mason, Ugo V. Boscain, and Yacine Chitour. Common polynomial lyapunov functions for linear switched systems. SIAM J. Control and Optimization, 45(1):226--245, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Eike Möhlmann and Oliver E. Theel. Stabhyli: a tool for automatic stability verification of non-linear hybrid systems. In Proceedings of the International Conference on Hybrid Systems: Computation and Control, pages 107--112, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Antonis Papachristodoulou and Stephen Prajna. On the construction of Lyapunov functions using the sum of squares decomposition. In Conference on Decision and Control, 2002.Google ScholarGoogle ScholarCross RefCross Ref
  14. Stefan Pettersson and Bengt Lennartson. Stability of hybrid systems using lmis - A gear-box application. In Proceedings of the International Conference on Hybrid Systems: Computation and Control, pages 381--395, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Andreas Podelski and Silke Wagner. Model checking of hybrid systems: From reachability towards stability. In Proceedings of the International Conference on Hybrid Systems: Computation and Control. Springer, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Andreas Podelski and Silke Wagner. Region stability proofs for hybrid systems. In Proceedings of Formal Modeling and Analysis of Timed Systems, pages 320--335, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Pavithra Prabhakar and Miriam García Soto. Abstraction based model-checking of stability of hybrid systems. In Proceedings of the International Conference on Computer Aided Verification, pages 280--295, 2013.Google ScholarGoogle ScholarCross RefCross Ref
  18. Pavithra Prabhakar and Miriam García Soto. Counterexample guided abstraction refinement for stability analysis. In Proceedings of the International Conference on Computer Aided Verification, 2016.Google ScholarGoogle ScholarCross RefCross Ref
  19. Pavithra Prabhakar and Miriam García Soto. Hybridization for stability analysis of switched linear systems. Proceedings of the International Conference on Hybrid Systems: Computation and Control, 2016. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. A. Puri, V.S. Borkar, and P. Varaiya. ε-approximation of differential inclusions. In Proceedings of the International Conference on Hybrid Systems: Computation and Control, pages 362--376, 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Weehong Tan and Andrew K. Packard. Stability region analysis using polynomial and composite polynomial lyapunov functions and sum-of-squares programming. IEEE Transactions on Automatic Control, 53(2):565--571, 2008.Google ScholarGoogle ScholarCross RefCross Ref

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  • Published in

    cover image ACM Other conferences
    EMSOFT '16: Proceedings of the 13th International Conference on Embedded Software
    October 2016
    260 pages
    ISBN:9781450344852
    DOI:10.1145/2968478

    Copyright © 2016 ACM

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    • Published: 1 October 2016

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