Error Bounds Based Stochastic Approximations and Simulations of Hybrid Dynamical Systems
Alessandro Abate, Aaron Ames, Shankar Sastry

Citation
Alessandro Abate, Aaron Ames, Shankar Sastry. "Error Bounds Based Stochastic Approximations and Simulations of Hybrid Dynamical Systems". Proceedings of the 25th American Control Conference, June, 2006.

Abstract
This paper introduces, develops and discusses an integration-inspired methodology for the simulation and analysis of deterministic hybrid dynamical systems. When simulating hybrid systems, and thus unavoidably introducing some numerical error, a progressive tracking of this error can be exploited to discern the properties of the system, i.e., it can be used to introduce a stochastic approximation of the original hybrid system, the simulation of which would give a more complete representation of the possible trajectories of the system. Moreover, the error can be controlled to check and even guarantee (in certain special cases) the robustness of simulated hybrid trajectories.

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Citation formats

• HTML

  Alessandro Abate, Aaron Ames, Shankar Sastry. <a
  href="http://chess.eecs.berkeley.edu/pubs/212.html"
  >Error Bounds Based Stochastic Approximations and
  Simulations of Hybrid Dynamical Systems</a>,
  Proceedings of the 25th American Control Conference, June,
  2006.

• Plain text

  Alessandro Abate, Aaron Ames, Shankar Sastry. "Error
  Bounds Based Stochastic Approximations and Simulations of
  Hybrid Dynamical Systems". Proceedings of the 25th
  American Control Conference, June, 2006.

• BibTeX

  @inproceedings{AbateAmesSastry06_ErrorBoundsBasedStochasticApproximationsSimulationsOf,
      author = {Alessandro Abate and Aaron Ames and Shankar Sastry},
      title = {Error Bounds Based Stochastic Approximations and
                Simulations of Hybrid Dynamical Systems},
      booktitle = {Proceedings of the 25th American Control Conference},
      month = {June},
      year = {2006},
      abstract = {This paper introduces, develops and discusses an
                integration-inspired methodology for the
                simulation and analysis of deterministic hybrid
                dynamical systems. When simulating hybrid systems,
                and thus unavoidably introducing some numerical
                error, a progressive tracking of this error can be
                exploited to discern the properties of the system,
                i.e., it can be used to introduce a stochastic
                approximation of the original hybrid system, the
                simulation of which would give a more complete
                representation of the possible trajectories of the
                system. Moreover, the error can be controlled to
                check and even guarantee (in certain special
                cases) the robustness of simulated hybrid
                trajectories.},
      URL = {http://chess.eecs.berkeley.edu/pubs/212.html}
  }
  

Posted by Alessandro Abate on 24 Apr 2007.
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