Advertisement

Automation and Remote Control

, Volume 65, Issue 7, pp 1037–1045 | Cite as

Coordinated Control of Networked Vehicles: An Autonomous Underwater System

  • F. Lobo Pereira
  • J. Borges de Sousa
Article

Abstract

The specification and design of coordinated control strategies for networked vehicle systems are discussed. The discussion is illustrated with an example of the coordinated operation of two teams of autonomous underwater vehicles collecting data to find the local minimum of a given oceanographic scalar field.

Keywords

Mechanical Engineer Local Minimum System Theory Scalar Field Underwater Vehicle 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

REFERENCES

  1. 1.
    de Sousa, J.B. and Sengupta, R., Cdc Tutorial on Autonomous and Semiautonoomous Networked Multivehicle Systems, 2001.Google Scholar
  2. 2.
    Pereira, F.L., Control Design for Autonomous Vehicles: A Dynamic Optimization Perspective, Eur. J.Control, 2001, no. 7, pp. 178–202.Google Scholar
  3. 3.
    Pereira, F.L. and de Sousa, J.B., Specification and Design of Coordinated Motions for Autonomous Vehicles, IEEE Conf. on Decision and Control Society, 2002.Google Scholar
  4. 4.
    Pereira, F.L., de Sousa, J.B., and Matos, A., Dynamic Optimization in the Coordination and Control of Autonomous Underwater Vehicles, IEEE Conf. on Decision and Control, 2002.Google Scholar
  5. 5.
    Aubin, J.-P., Viability Theory, Boston: Birkhauser, 1991.Google Scholar
  6. 6.
    Clarke, F.N. et al., Nonsmooth Analisis and Control Theory, New York: Springer, 1998.Google Scholar
  7. 7.
    Clarke, F.H., Optimization and Nonsmoth Analisis, Philadelphia: SIAM, 1990.Google Scholar
  8. 8.
    Clarke, F.H., A Proximal Characterization of the Reachable Set, Syst. Control Lett., 1996, vol. 27,no. 3, pp. 195–197.CrossRefGoogle Scholar
  9. 9.
    Clarke, F.H. and Wolenski, P.R., Control of Systems to Sets and Their Interiors, J. Optimiz. Theory Appl., 1996, vol. 88, no. 1, pp. 3–23.Google Scholar
  10. 10.
    Clarke, F.H., Ledyaev, Y.S., and Subbotin, A.I., The Synthesis of Universal Feedback Pursuit Strategies in Differential Games, SIAM J. Control Optimiz., 1997, vol. 35, no. 2, pp. 52–61.Google Scholar
  11. 11.
    Krasovskii, A.N., Control under Lack of Information, Boston: Birkhauser, 1995.Google Scholar
  12. 12.
    Advances in Nonlinear Dynamics and Control: A Report from Russia, Kurzhanskii, A.B., Ed., Boston: Birkhauser, 1993.Google Scholar
  13. 13.
    Kurzhanskii, A.B., Ellipsoidal Calculus for Estimation and Control, Boston: Birkhauser, 1997.Google Scholar
  14. 14.
    Fossen, T.I., Guidance and Control of Ocean Vehicles, New York: Wiley, 1994.Google Scholar
  15. 15.
    Principles of Naval Architecture, Lewis, E., Ed., Society of Naval Architects and Marine Engineers, 1989.Google Scholar
  16. 16.
    Bardi, M. and I. Capuzzo-Dolcetta, I., Optimal Control and Viscosity Solutions of Hamilton-Jacobi-Bellman Equations, Boston: Birkhauser, 1997.Google Scholar
  17. 17.
    Evans, L.C., Partial Differential Equations. Graduate Studies in Mathematics, Providence: AMS, 1998.Google Scholar
  18. 18.
    Krasovskii, N.N. and Subbotin, A.I., Game-theoretical Control Problems, New York: Springer-Verlag, 1988.Google Scholar
  19. 19.
    Subbotin, A.I., Generalized Solutions of First-order PDEs: The Dynamical Optimization Perspective, Boston: Birkhauser, 1995.Google Scholar
  20. 20.
    Van Cleave, D., Trends and Technologies for Uninhabited Autonomous Vehicles, in Software-Enabled Control: Information Technology for Dinamical Systems, Samad, T. and Balas. G., <nt>Eds</nt>., New York: Wiley, 2002.Google Scholar

Copyright information

© MAIK “Nauka/Interperiodica” 2004

Authors and Affiliations

  • F. Lobo Pereira
  • J. Borges de Sousa

There are no affiliations available

Personalised recommendations