Fuzzy Logic pp 253-262 | Cite as

Reasoning and Analysis of Uncertainties within Command and Control Navigation Simulation Using Fuzzy Logic Petri Net

  • Amir M. Anvar
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 81)


The main objective of this paper is to study and design a methodology to apply a fuzzy logic Petri Net approach to handle approximation and uncertainty within command and control navigation processes in a simulation environment. The design of this study is to provide a fundamental decision support system within a command and control object in a distributed simulation framework. In particular, due to inherent uncertainties within a navigation simulation strategy it is essential to design a system that uses intuitive approaches to navigation. In this investigation Petri Net is used as a simulation tool to explore the use of fuzzy logic in autonomous command and control within navigation problems. This framework also highlights the reasoning used to decide the most appropriate path from various navigation routes. The outcomes are beneficial in several areas including auto-navigation simulation within command and control systems.


Membership Function Fuzzy Logic Radar Sensor Autonomous Helicopter Navigation Direction 
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  1. 1.
    Jensen, K. (1995). Coloured Petri Nets, Basic Concepts, Analysis Methods and Practical Use, Vol. 1, 2 and 3 Springer-Verlag, Berlin, Heidelberg.Google Scholar
  2. 2.
    Peterson, J. (1977) Petri Nets, Computer Surveys, Vol. 9, No. 3Google Scholar
  3. 3.
    Jensons, K. Coloured Petri Nets, Basic Concepts, Analysis Methods and Practical Use, Vol. 3 Springer-Verlag, Berlin, Heidelberg, (1997).CrossRefGoogle Scholar
  4. 4.
    Takagi, T. and Sugeno, M. (1985) “Fuzzy identification of Systems and its applications to modelling and control”, IEEE Transactions on Systems, Manual, Cybernetics, SMC-15: 116–32Google Scholar
  5. 5.
    Zadeh, L, (1965) Fuzzy Sets, Inform. Contr.,8(3):388–353, JuneGoogle Scholar
  6. 6.
    Zadeh, L. (1978) Fuzzy Sets as a Basis for a Theory of Possibility, Fuzzy Sets and Systems, 1: 3–28MathSciNetMATHCrossRefGoogle Scholar
  7. 7.
    James, P. (1977) Petri Nets, ACM Computing Surveys. 9, 3, 223–252MATHCrossRefGoogle Scholar
  8. 8.
    Petri, C. 1962 Kommunikation mit automaten PhD dissertation. Bobb: Institut fur Instrumentelle Mathematik. (English translation: Communication with automata, Technical Report, RADC-TR-65–377, vol. 1, Suppl. 1. New York: Griffiss Air Force Base, 1966 )Google Scholar
  9. 9.
    Coa, T. and Sanderson, A. (1993) Variable Reasoning and Analysis about Uncertainty with Fuzzy Petri Nets, Proc. 14` h International Conference, USAGoogle Scholar
  10. 10.
    Coa, T. and Sanderson, A. (1995) Task Sequence Planning Using Fuzzy Petri Nets, IEEE Transaction. on System Man and Cybernetics, Vol. 25, No. 5. 755–768CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Amir M. Anvar
    • 1
  1. 1.Aeronautical and Maritime Research LaboratoryDefence Science and Technology OrganisationSalisburyAustralia

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