A Logic-Based Approach to Model Supervisory Control Systems

  • Pierangelo Dell’Acqua
  • Anna Lombardi
  • Luís Moniz Pereira
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4203)


We present an approach to model supervisory control systems based on extended behaviour networks. In particular, we employ them to formalize the control theory of the supervisor. By separating the reasoning in the supervisor and the action implementation in the controller, the overall system architecture becomes modular, and therefore easily changeable and modifiable.


Integrity Constraint Supervisory Control Behaviour Network Controller Choice Extended Behaviour 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Antsaklis, P.J., Nerode, A.: Hybrid control systems: An introductory discussion to the special issue. IEEE Transactions on Automatic Control 43(4), 457–460 (1998)CrossRefMathSciNetGoogle Scholar
  2. 2.
    Brooks, R.A.: A robust layered control system for a mobile robot. IEEE J. of Robotics and Automation 2(1), 14–23 (1986)CrossRefGoogle Scholar
  3. 3.
    Dell’Acqua, P., Lombardi, A., Pereira, L.M.: Modelling Hybrid Control Systems with Behaviour Networks. In: Filipe, J., Ferrier, J.-L., Cetto, J.A. (eds.) 2nd Int. Conf. on Informatics in Control, Automation and Robotics (Icinco 2005). Procs. Intelligent Control Systems and Optimization, vol. 1, pp. 98–105. INSTICC Press (2005) ISBN:972-8865-29-5Google Scholar
  4. 4.
    Franklin, S.: Artificial Minds. MIT Press, Cambridge (1995)Google Scholar
  5. 5.
    Hespanha, J.P., Liberzon, D., Morse, A.S.: Overcoming the limitations of adaptive control by means of logic-based switching. Systems and Control Letters (to appear)Google Scholar
  6. 6.
    Kohn, W., Nerode, A.: Models for hybrid systems: automata, topologies, controllability and observability. In: Grossman, R.L., Ravn, A.P., Rischel, H., Nerode, A. (eds.) HS 1991 and HS 1992. LNCS, vol. 736, pp. 317–356. Springer, Heidelberg (1993)Google Scholar
  7. 7.
    Kohn, W., Nerode, A.: Multiple agent hybrid control architecture. In: Grossman, R.L., Ravn, A.P., Rischel, H., Nerode, A. (eds.) HS 1991 and HS 1992. LNCS, vol. 736, pp. 297–316. Springer, Heidelberg (1993)Google Scholar
  8. 8.
    Lin, F.: Robust and adaptive supervisory control of discrete event systems. IEEE Transactions on Automatic Control 38(12), 1848–1852 (1993)MATHCrossRefGoogle Scholar
  9. 9.
    Maes, P.: How to do the right thing. Connection Science Journal, Special Issue on Hybrid Systems 1(3), 291–323 (1989)Google Scholar
  10. 10.
    Maes, P.: A bottom-up mechanism for behavior selection in an artificial creature. In: Meyer, J.A., Wilson, S. (eds.) Proceedings of the first International Conference on Simulation of Adaptive Behavior, MIT Press, Cambridge (1991)Google Scholar
  11. 11.
    Minsky, M.: The Society of Mind. Simon and Schuster, New York (1986)Google Scholar
  12. 12.
    Tu, X.: Artificial Animals for Computer Animation: Biomechanics, Locomotion, Perception, and Behavior. PhD thesis, ACM Distinguished Ph.D Dissertation Series, LNCS, vol. 1635 (1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Pierangelo Dell’Acqua
    • 1
    • 2
  • Anna Lombardi
    • 1
  • Luís Moniz Pereira
    • 2
  1. 1.Department of Science and Technology – ITNLinköping UniversityNorrköpingSweden
  2. 2.Centro de Inteligência Artificial – CENTRIA, Departamento de Informática, Faculdade de Ciências e TecnologiaUniversidade Nova de LisboaCaparicaPortugal

Personalised recommendations