Hybrid automata: from verification to implementation

  • Stanley Bak
  • Omar Ali Beg
  • Sergiy Bogomolov
  • Taylor T. Johnson
  • Luan Viet Nguyen
  • Christian Schilling
Regular Paper

Abstract

Hybrid automata are an important formalism for modeling dynamical systems exhibiting mixed discrete–continuous behavior such as control systems and are amenable to formal verification. However, hybrid automata lack expressiveness compared to integrated model-based design frameworks such as the MathWorks’ Simulink/Stateflow (SlSf). In this paper, we propose a technique for correct-by-construction compositional design of cyber-physical systems (CPS) by embedding hybrid automata into SlSf models. Hybrid automata are first verified using verification tools such as SpaceEx and then automatically translated to embed the hybrid automata into SlSf models such that the properties verified are transferred and maintained in the translated SlSf model. The resultant SlSf model can then be used for automatic code generation and deployment to hardware, resulting in an implementation. The approach is implemented in a software tool building on the HyST model transformation tool for hybrid systems. We show the effectiveness of our approach on a CPS case study—a closed-loop buck converter—and validate the overall correct-by-construction methodology: from formal verification to implementation in hardware controlling an actual physical plant.

Keywords

Hybrid automata Model-based design Simulink/Stateflow 

Notes

Acknowledgements

The authors thank the anonymous reviewers for their insightful comments. The material presented in this paper is based upon work supported by the Air Force Office of Scientific Research (AFOSR), in part under contract numbers FA9550-15-1-0258 and W911NF-16-1-0534, by AFRL through contract number FA8750-15-1-0105, by the National Science Foundation (NSF) under Grant Numbers CNS 1464311, EPCN 1509804, and CCF 1527398, and by the ARC Project DP140104219 “Robust AI Planning for Hybrid Systems”. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of AFRL, AFOSR, or NSF.

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Copyright information

© US Government (outside the USA) 2017

Authors and Affiliations

  • Stanley Bak
    • 1
  • Omar Ali Beg
    • 2
  • Sergiy Bogomolov
    • 3
  • Taylor T. Johnson
    • 4
  • Luan Viet Nguyen
    • 2
  • Christian Schilling
    • 5
  1. 1.Air Force Research LaboratoryDaytonUSA
  2. 2.University of Texas at ArlingtonArlingtonUSA
  3. 3.Australian National UniversityCanberraAustralia
  4. 4.Vanderbilt UniversityNashvilleUSA
  5. 5.University of FreiburgFreiburg im BreisgauGermany

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