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Hybrid cc with interval constraints

  • Björn Carlson
  • Vineet Gupta
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1386)

Abstract

Hybrid cc is a constraint programming language suitable for modeling, controlling and simulating hybrid systems, i.e. systems with continuous and discrete state changes. The language extends the con-current constraint programming framework with default reasoning and combinators for programming continuous behavior. The most important constraint systems used in Hybrid cc are nonlinear equations and ordinary differential equations over intervals. We describe the implementation of the Hybrid cc interpreter and constraint solvers, and evaluate the performance using some example programs.

Keywords

Constraint Programming Interval Arithmetic Reduction Rule Point Phase Default Reasoning 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [ACH+95]
    R. Alur, C. Courcoubetis, N. Halbwachs, T.A. Henzinger, P.-H. Ho, X. Nicollin, A. Olivero, J. Sifakis, and S. Yovine. The algorithmic analysis of hybrid systems. Theoretical Computer Science, 138:3–34, 1995.Google Scholar
  2. [AH83]
    Gotz Alefeld and Jurgen Herzberger. Introduction to Interval Computations. Academic Press, 1983.Google Scholar
  3. [BB91]
    A. Benveniste and G. Berry. The synchronous approach to reactive and real-time systems. Proceedings of the IEEE, 79(9):1270–1282, September 1991.Google Scholar
  4. [Car95]
    Bjorn Carlson. Compiling and Executing Finite Domain Constraints. PhD thesis, Uppsala University, 1995.Google Scholar
  5. [Cor95]
    G. F. Corliss. Guaranteed error bounds for ordinary differential equations. In W.A.Light and M.Marletta, editors, Theory of Numerics in Ordinary and Partial Differential Equations, volume IV of Advances in Numerical Analysis, pages 1–75. Oxford University Press, 1995.Google Scholar
  6. [DGS96]
    Akash Deshpande, Aleks Gollu, and Luigi Semenzato. The SHIFT programming language and run-time system for dynamic networks of hybrid automata. Technical report, UC Berkeley PATH Project, 1996. www-path.eecs.berkeley.edu/shift/doc/ieeshift.ps.Google Scholar
  7. [GJS97]
    Vineet Gupta, Radha Jagadeesan, and Vijay Saraswat. Computing with continuous change. Science of Computer Programming, 1997. To appear. Available from http://ic.arc.nasa.gov/people/vgupta.Google Scholar
  8. [GJSB95]
    Vineet Gupta, Radha Jagadeesan, Vijay Saraswat, and Daniel Bobrow. Programming in hybrid constraint languages. In Panos Antsaklis, Wolf Kohn, Anil Nerode, and Sankar Sastry, editors, Hybrid Systems II, volume 999 of Lecture notes in computer science. Springer Verlag, November 1995.Google Scholar
  9. [GSS95]
    Vineet Gupta, Vijay Saraswat, and Peter Struss. A model of a photocopier paper path. In Proceedings of the 2nd IJCAI Workshop on Engineering Problems for Qualitative Reasoning, August 1995.Google Scholar
  10. [Hal93]
    N. Halbwachs. Synchronous programming of reactive systems. The Kluwer international series in Engineering and Computer Science. Kluwer Academic publishers, 1993.Google Scholar
  11. [Har87]
    D. Harel. Statecharts: A visual approach to complex systems. Science of Computer Programming, 8:231–274, 1987.CrossRefGoogle Scholar
  12. [HSD92]
    Pascal Van Hentenryck, Vijay A. Saraswat, and Yves Deville. Constraint processing in cc(fd). Technical report, Computer Science Department, Brown University, 1992.Google Scholar
  13. [Jan94]
    S. Janson. AKL — A Multiparadigm Programming Language. PhD thesis, Uppsala University, 1994.Google Scholar
  14. [Kay96]
    Herbert Kay. Refining Imprecise Models and Their Behaviors. PhD thesis, University of Texas at Austin, 1996.Google Scholar
  15. [PTVF92]
    W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery. Numerical Recipes in C. Cambridge University Press, 1992.Google Scholar
  16. [Rei80]
    Ray Reiter. A logic for default reasoning. Artificial Intelligence, 13:81–132, 1980.CrossRefGoogle Scholar
  17. [Sar93]
    Vijay A. Saraswat. Concurrent constraint programming. Doctoral Dissertation Award and Logic Programming Series. MIT Press, 1993.Google Scholar
  18. [SDG96]
    Luigi Semenzato, Akash Deshpande, and Aleks Gollu. The SHIFT reference manual. Technical report, UC Berkeley PATH Project, 1996. www-path.eecs.berkeley.edu/shift/doc/shift.ps.gz.Google Scholar
  19. [SJG96]
    V. A. Saraswat, R. Jagadeesan, and V. Gupta. Timed Default Concurrent Constraint Programming. Journal of Symbolic Computation, 22(5–6):475–520, November/December 1996. Extended abstract appeared in the Proceedings of the 22nd ACM Symposium on Principles of Programming Languages, San Francisco, January 1995.Google Scholar
  20. [vHLB97]
    Pascal van Hentenryck, Michel Laurent, and Frederic Benhamou. Newton: Constraint programming over non-linear constraints. Science of Programming, 1997. to appear.Google Scholar
  21. [VMK95]
    Pascal Van Hentenryck, David McAllester, and D. Kapur. Solving polynomial systems using a branch and prune approach. SIAM Journal of Numerical Analysis, 1995. (Accepted). (Also available as Brown University technical report CS-95-O1.).Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Björn Carlson
    • 1
  • Vineet Gupta
    • 2
  1. 1.Netscape CommunicationsMountain ViewUSA
  2. 2.NASA Ames Research CenterCaelum Research CorporationMoffett FieldUSA

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