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Fuzzified Petri-Nets and Their Application to Organising Supervisory Controller

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Computational Intelligence: Soft Computing and Fuzzy-Neuro Integration with Applications

Part of the book series: NATO ASI Series ((NATO ASI F,volume 162))

Abstract

A model and the decision reasoning processes of a two-layer organising supervisory controller for complex systems have been developed. It is based on fuzzy Petri-net algorithms and fuzzy rule production system for decision and command control. This model follows the fundamental idea of the original intelligent controller of G.N. Saridis, but adds on a new generic property. This fuzzy-Petri-net organising controller employs the advantages of both the qualitative modelling potential of L.A. Zadeh’s fuzzy logic and of the discrete-event genesis of K.A. Petri’s networks. Thus it accomplishes full compatibility of mathematical formalisms of the organising and co-ordinating levels of G.N. Saridis’ architecture and greatly reduces the rules needed due to possibility distribution evaluation and Petri-net-supported reasoning in comparison with Stellakis-Valavanis fuzzy solution for the organiser.

Articlefootnote

This contribution is dedicated to Professor Lotfi A.ZADEH

“To Lotfi Zadeh

Who had the courage and the gift

To begin the grand paradigm shift

And to many others

Whose hard work and healthy thinking

Have contributed to the shifting“ (Professor George J. Klir, 1995)

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References

  1. Ashby, W.R.: Design for a Brain. New York: J. Wiley 1952

    Google Scholar 

  2. Ashby, W.R.: Information flow within co-ordinated systems. In J. Rose (ed.) Progress in Cybernetics. London: Gordon & Bearch 1970, pp. 57–64

    Google Scholar 

  3. Astrom, K.J., J.J. Anton & K.E. Arzen: Expert control. Automatica 22, 227–236 (1986)

    Article  Google Scholar 

  4. Astrom, K.J.: Towards intelligent control. IEEE Contr. Syst. Mag. 9, 60–64 (1989)

    Article  Google Scholar 

  5. Astrom, K.J.: Intelligent control. In: I.D. Landau et al. (eds.) 1st European Control Conference. Proceedings, Grenoble 1991, 3, 2328–2339. Paris: Hermes 1991

    Google Scholar 

  6. Baldwin, J.F.: A new approach to approximate reasoning using a fuzzy logic. Fuzzy Sets & Syst. 2, 309–328 (1979)

    Article  MathSciNet  MATH  Google Scholar 

  7. Bugarin, A.J. & S. Barro, Fuzzy reasoning supported by Petri nets. IEEE Trans. Fuzzy Systems 2, 135–150 (1994)

    Article  Google Scholar 

  8. Cao, T. & A.C. Anderson: A fuzy petri net approach to reasoning about uncertainty in robotic systems. In: IEEE Int. Conf. Robotics and Automation. Proceedings, Atlanta GA 1993, 317–322. New York: IEEE 1993

    Google Scholar 

  9. Cao, T. & A.C. Anderson: Task sequence planning using fuzzy Petri nets. IEEE Trans. Syst. Man Cybern. 25, 755–768 (1995)

    Article  Google Scholar 

  10. Chen, S.M., J.S. Ke & J.F. Chang: Knowledge representation using fuzzy Petri nets. IEEE Trans. Know. Data Eng. 2, 311–319 (1990)

    Article  Google Scholar 

  11. Conant, R.C.: Laws of information that govern systems. IEEE Trans. Syst. Man Cybern. 6, 240–255 (1976)

    MathSciNet  MATH  Google Scholar 

  12. Dimirovski, G.M., N.E. Gough & S. Barnett: Categories in systems and control theory. Int.J. Syst. Sci. 8, 1081–1090 (1977)

    Article  MATH  Google Scholar 

  13. Dimirovski, G.M., B.L. Crvenkovski & D.M. Joskovski: Expert system for recognition and typical identification of dynamic process models. In: R. Husson (ed.) Advanced Information Processing in Automatic Control. Proceedings of Selected Papers, Nancy 1989, 257–262. Oxford: The IFAC & Pergamon Press 1990

    Google Scholar 

  14. Dimirovski, G.M.: Towards intelligent control and expert computer-aided systems engineering (Invited Plenary Peper) In: Proc. 36th Yugoslav Conf. ETAN. Proceedings of Selected Papers, Ohrid 1991, I, 27–42. Belgrade (Sr-SFRY): The ETAN Association 1991

    Google Scholar 

  15. Dimirovski, G.M. et al.: Knowledge-based closed-loop process identifier via pattern recognition. In: P. Albertos & P. Kopacek (eds.) Low Cost Automation Techniques and Applications, Proceedings of Selected Papers, Vienna 1992, 125–128. Oxford: The IFAC & Pergamon Press 1992

    Google Scholar 

  16. Dimirovski, G.M. et al: Modelling and scheduling of FMS based on stochastic Petri—nets. In: R.Evans (ed.) 12th IFAC World Congress. Proceedings, Sydney 1993, II, 117–120. Barton Act (AUS): The IFAC & The Instn. Engrs. Australia 1993

    Google Scholar 

  17. Dimirovski, G.M. et al.: Fuzzy-logic control algorithms in navigation of a factory floor vehicle-robot. In: IEE Publication No 389. Proceedings, Coventry 1994, 1, 282–287. London: The Instn. Electr. Engrs. 1994

    Google Scholar 

  18. Dimirovski, G.M. et al.: A generic fuzzy controller for multivariable processes. In: G. Buja (Gen.Chairman) IEEE Conference IECON 94. Proceedings, Bologna 1994, 2, 1359–1364. New York: IEEE 1994

    Google Scholar 

  19. Dimirovski, G.M. et al.: Contributions to two-level intelligent non-linear control systems. In: O. Kaynak et al. (eds.) Recent Advances in Mechatronics. Proceedings, Istanbul 1995, II, 874–881. Istanbul: UNESCO Chair Mechatronics Bogazici Uniiversity 1995

    Google Scholar 

  20. Dimirovski, G.M. et al.: Contributions to intelligent supervision and control for saving energy. In: P.D. Roberts & J.E. Ellis (eds.) IFAC Int. Symp. on Large Scale Systems. Proceedings of Selected Papers, London 1995, 1, 59–60. Oxford: The IFAC & Elsevier Science 1995

    Google Scholar 

  21. Dimirovski, G.M. et al.: Optimum supervisory control of low-power multi-machine hydroelectric plants. In: P.D. Roberts & J.E. Ellis (eds.) IFAC Int. Symp. on Large Scale Systems. Proceedings of Selected Papers, London 1995, 2, 911–916. Oxford: The IFAC & Elsevier Science 1995

    Google Scholar 

  22. Dimirovski, G.M., R. Hanus & R.M. Henry: Complex systems control in energy, industry and transport technologies: Contributions to intelligent automation. Journal E.C.&T. Engineering 1, 1–22 (1996)

    Google Scholar 

  23. Dimirovski, G.M., R. Hanus & R.M. Henry: A two-level system for intelligent automation using fuzzified Petri-nets and non-linear systems. In: M.Jamshidi (Gen. Chairman & ed.) Proceedings WAC96, TSI Press Series Robotics and Manufacturing. Proceedings of Selected Papers, Montpellier 1996, Paper WdA13–5. Albuquerke NM: The TSI Press 1996

    Google Scholar 

  24. Dubois, D. & H. Prade, Possibility Theory. New York: Plenum Press 1988

    Book  MATH  Google Scholar 

  25. Dubois, D. & H. Prade: Fuzzy sets in approximate reasoning: Inference with possibility distributions, Pt. 1. Fuzzy Sets & Syst. 40, 143–202 (1991)

    Article  MathSciNet  MATH  Google Scholar 

  26. Einstein, A.: Remarks on Bertrand Russell’s theory of knowledge. In: P.A. Schlipp (ed.) The Philosophy of Bertrand Russell. Evanston IL: Northwestern University 1944, pp. 211–232

    Google Scholar 

  27. Fu, K.S.: Learning control systems — Review and outlook. IEEE Trans. Automat. Contr. 14, 210–220 (1970)

    Google Scholar 

  28. Gacovski, Z.M. et al.: A contribution to fuzzy-Petri-net of the intelligent organizing controller. In: M.Smiljanic et al. (eds.) XL Conference ETRAN. Proceedings of Selected Papers, Budva 1996, IV, 259–262. Belgrade (Yu): Society for Electron., Telecomm., Comput., Automat. and Nuclear Engng. 1996

    Google Scholar 

  29. Gacovski, Z.M.: Fuzzy-Petri-Net Based Organising Coordination Level in the Intelligent Control of Robotic Systems. St. Cyril & St. Methodius University, Faculty of EE, Skopje, ASE Techn. Rep. FPN—IC/96–3, December 1996

    Google Scholar 

  30. Gaines, B.R.: Foundations of fuzzy reasoning. Int. J. Man-Machine Stud. 8, 227–256 (1976)

    MathSciNet  Google Scholar 

  31. Garg, M.L., S.I. Ashon & P.V. Gupta: A fuzzy Petri net for knowledge representation and reasoning. Inf. Process. Lett. 39, 165–171 (1991)

    MATH  Google Scholar 

  32. Gitt, W.: Information: the third fundamental quantity. Siemens Review 56, 36–41 (1987)

    Google Scholar 

  33. Godel, K.: Russell’s mathematical logic. In: P. Benaceraff & H. Putnam (eds.) Phillosophy of Mathematics. Englewood Cliffs NJ: Prentice-Hall 1964, pp. 211–232

    Google Scholar 

  34. Harris, C.J., C.G. Moore & M. Brown: Intelligent Control: Aspects of Fuzzy Logic and Neural Nets. Singapore: World Scientific Press 1993

    MATH  Google Scholar 

  35. Harris, C.J.: Advances in Intelligent Control. London: Taylor & Francis 1994.

    MATH  Google Scholar 

  36. Harris, C.J. and T.E. Schilhabe: Advances and critical research issues in intelligent modelling, control and estimation. In: M. Thoma & R. Patton (eds.) First Joint Workshop on COSY Programme of the ESF. Proceedings, Roma 1995,46–51. Rome: European Science Foundation and Universita La Sapienza 1995

    Google Scholar 

  37. Hirota, K. & W. Pedrycz: Referential modes of reasoning. In: Proc. 2nd IEEE Int. Conf. on Fuzzy Systems. Proceedings, San Francisco, 1993, 558–563. New York: The IEEE 1993

    Google Scholar 

  38. Klawon, F.: Fuzzy sets and vague environments. Fuzzy Sets & Syst. 66, 207–221 (1994)

    Article  MATH  Google Scholar 

  39. Klir, G.J. & B. Yuan: Fuzzy Sets and Fuzzy Logic: Theory and Applications. Upper Sadie River NJ: Prentice-Hall 1995

    MATH  Google Scholar 

  40. Kolmogorov, A.N.: Logical basis for information theory and probability theory. IEEE Trans. Inform. Theory 16, 662–664 (1968)

    Article  MathSciNet  Google Scholar 

  41. Krijgsman, A.J., R. Jager & H.B. Verbrugen: Real-time autonomous control. In: R.Evans (ed.) 12th IFAC World Congress. Proceedings, Sydney 1993, I, 119–122. Barton Act (AUS): The IFAC & The Instn. Engrs. Australia 1993

    Google Scholar 

  42. Kruse, R., J. Gebhardt & F. Klawon: Foundations of Fuzzy Systems. Chichester: J.Wiley 1994

    Google Scholar 

  43. Kuipers, B. & K.J. Astrom: The composition and validation of heterogeneous control laws. Automatica 30, 233–249 (1994)

    Article  MATH  Google Scholar 

  44. Lee, C.C.: Fuzzy logic in control systems: Fuzzy logic controller, Pts. I & II. IEEE Trans. Syst. Man Cybern. 20, 404–418 and 419–432 (1990)

    Article  MATH  Google Scholar 

  45. Lee, C.C.: A self-learning rule-based controller employing approximate reasoning and neural net concepts. Int.J. Intell. Syst. 6, 71–93 (1991)

    Article  Google Scholar 

  46. Looney, C.G.: Fuzzy Petri-nets for rule based decision making. IEEE Trans. Syst. Man Cybern. 18, 178–183 (1988)

    Article  Google Scholar 

  47. MacFarlane, A.G.J.: Information, knowledge and control. In: H.L. Trentelmann & J.C.Willems (eds.) Essays on Control Theory: Perspectives in the Theory and Its Applications. Boston: Birkhauser, 1993, pp. 1–28

    Google Scholar 

  48. Mamdani, E.H. & S.Assilian: An experiment in lingustic synthesis with a fuzzy logic controller. Int.J. Man-Mach. Stud. 7, 1–13 (1974)

    Article  Google Scholar 

  49. Mamdani, E.H.: Advances in the linguistic synthesis of fuzzy controllers. Int. J. Man-Mach. Stud. 8, 669–678 (1976)

    Article  MATH  Google Scholar 

  50. Mamdani, E.H.: Application of fuzzy logic to approximate reasoning using linguistic synthesis. IEEE Trans. Computer 6, 1182–1191 (1977)

    Article  Google Scholar 

  51. Mamdani, E.H.: Twenty years of fuzzy control: Experiences gained and lessons learnt (Invited Paper). In: R.J.Markus II (ed.) Fuzzy Logic Technology and Applications. New York: The IEEE 1994, pp. 19–24

    Google Scholar 

  52. Mesarovic, M.D. D. Macko & Y. Takahara: Theory of Multilevel Systems. New York: Academic 1970

    MATH  Google Scholar 

  53. Meystel, A.: Intelligent control in robotics. J. Robotic Syst. 5,269–308,1988

    Google Scholar 

  54. Meystel, A.: Intelligent control: A sketch of the theory. J. Intell. Robot. Syst. Theory & Appl. 2, 97–107 (1989)

    Google Scholar 

  55. Murata, T.: Petri nets: Properties, analysis, and applications. IEEE Proceedings 77, 541–580 (1991)

    Article  Google Scholar 

  56. Pascal, J.-C., R. Valette & D. Andreu: Fuzzy sequential control based on Petri nets. In: IEEE Conf. Emerging Technologies and Factory Automation. Proceedings, 140–145. New York: The IEEE 1992

    Google Scholar 

  57. Pedrycz, W. & F. Gromide: A generalized fuzzy Petri net model. IEEE Trans. Fuzzy Systems 2, 295–301 (1994)

    Article  Google Scholar 

  58. Petri, C.A.: Kommunikation mit Automaten. Schriften des Reinisch-Westfalischen Institut fur Instrumentelle Mathematik, Heft 2. Bonn: Universitat Bonn 1962

    Google Scholar 

  59. Peterson, J.L.: Petri Nets Theory and the Modeling of Systems. Englewood Cliffs NJ: Prentice-Hall 1981

    Google Scholar 

  60. Russell, B.: Vagueness. Australas. J. Psychol. Phylosophy 1, 84–92 (1923)

    Google Scholar 

  61. Saridis, G.N.: Towards realisation of intelligent controls. Proceedings IEEE 67, 11151133(1979)

    Google Scholar 

  62. Saridis, G.N.: Entropy formulation of optimal and adaptive control. IEEE Trans. Autom. Contr. 33, 713–721 (1988)

    Article  MathSciNet  Google Scholar 

  63. Saridis, G.N.: Analytical formulation of the principle of increasing precision with decreasing intelligence. Automatica 25, 461–467 (1989)

    Article  MATH  Google Scholar 

  64. Saridis, G.N.: Theory of intellgent machines (Special Lecture). In: O. Kaynak (ed.) IEEE Workshop Intelligent Motion Control, Proceedings, Istanbul 1990, I, SL. (1930). New York: The IEEE 1990

    Google Scholar 

  65. Saridis, G.N. & K.P. Valavanis: Analytical design of intelligent machines. Automatica 24, 123–133 (1988)

    Article  MATH  Google Scholar 

  66. Scarpelli, H., F. Gromide & R.R. Yager: A reasoning algorithm for high-level fuzzy Petri nets. IEEE Trans. Fuzzy Systems 4, 282–294 (1996)

    Article  Google Scholar 

  67. Stankovski, M.J. et al.: Modelling, simulation and control system design for a pipe reheating furnace. In: M. Hadjiiski (ed.) Automatics and Informatics 95. Proceedings of Scientific Papers, Sofia 1995, 76–83. Sofia: National Union for Automatics & Informatics of Bulgaria and Technical University of Sofia 1995

    Google Scholar 

  68. Stankovski, M.J. et al.: Simulation modelling of complex systems for exploring intelligent controls. In: M.H. Hamza (ed.) Modeling, Identfication and Control. Proceedings of Selected Papers, Innsbruck 1996, 212–216. Calgary - Zurich: The IASTED & Acta Press 1996

    Google Scholar 

  69. Stellakis, H.M. & K.P. Valavanis: Fuzzy-logic based formulation of the organizer for intelligent robotic systems. J. Intell. Robotic Syst. Theor. & Appl. 4, 1–24 (1991)

    Article  Google Scholar 

  70. Sugeno, M. & M.Nishida: Fuzzy control of a model car. Fuzzy Sets & Syst. 16, 103113(1985)

    Google Scholar 

  71. Sugeno, M. (ed.): Industrial Applications of Fuzzy Control. Amsterdam: Elsevier Science BV 1985

    Google Scholar 

  72. Tabak, D.: Petri-net representation od decision models. IEEE Trans. Syst. Man Cybern. 15, 812–818 (1985)

    Article  Google Scholar 

  73. Tsien, H.-S.: Engineering Cybernetics. New York: McGraw-Hill 1950

    Google Scholar 

  74. Turksen, B.I.: Approximate reasoning for production planning. Fuzzy Sets & Sys. 26, 23–37 (1988)

    Article  MathSciNet  MATH  Google Scholar 

  75. Turksen, B.I.: Measurement of membership functions and their acquisition. Fuzzy Sets & Sys. 40, 5–38 (1991)

    Article  MathSciNet  MATH  Google Scholar 

  76. Tzypkin, Y.Z.: Foundation of Self-Learning Systems (in Russian). Moskva: Nauka 1970

    Google Scholar 

  77. Valavanis, K.P. & G.N. Saridis: Information-theoretic modeling of intelligent robotic systems. IEEE Trans. Syst. Man. Cybern. 18, 852–872 (1988).

    Article  MathSciNet  Google Scholar 

  78. Valete, R., J. Cardoso & D. Dubois: Monitoring manufacturing systems by means of Petri nets with imprecise markings. In: IEEE Int. Symp. Intelligent Control. Proceedings, Albany NY, 1989, 233–237. New York: The IEEE 1989

    Google Scholar 

  79. Vukobratovic, M.K. & G.M. Dimirovski: Modelling simulation and control of robots and robotized FMS (Invited Plenary Lecture IPL-3). In: A. Kuzucu, I. Eksin & A.T. Dinibutun (eds.) IFAC Int. Workshop ACQP’92. Proceedings, Istanbul 1992, Late Paper IPL-3. (1–33). Istanbul: The IFAC & Istanbul Technical University 1992

    Google Scholar 

  80. Yager, R.R. On a general class of fuzzy connectives. Fuzzy Sets Syst. 4, 235–242, 1980

    Article  MathSciNet  MATH  Google Scholar 

  81. Yager, R.R.: Using approximate reasoning to represent dafault knowledge. Artificial Intell. 31, 99–112 (1987)

    Article  MathSciNet  MATH  Google Scholar 

  82. Yager, R.R., D.P. Filev & T. Saghedi: Analysis of flexible structured fuzzy logic controllers. IEEE Trans. Syst. Man Cybern. 24, 1035–1043 (1994)

    Article  Google Scholar 

  83. Yu, S.-K.: Knowledge representation and reasoning using fuzzy Pr/T net-systems. Fuzzy Sets & Syst. 75, 33–45 (1995)

    Article  MATH  Google Scholar 

  84. Zadeh, L.A.: Fuzzy sets. Informat. Contr. 8, 338–353 (1965)

    Article  MathSciNet  MATH  Google Scholar 

  85. Zadeh, L.A.: Quantitative fuzzy semantics. Informat. Sci. 3, 159–176 (1971)

    Article  MathSciNet  MATH  Google Scholar 

  86. Zadeh, L.A.: Outline of a new approach to the analysis of complex systems and decision processes. IEEE Trans. Syst. Man Cybern. 3, 28–44 (1973)

    Article  MathSciNet  MATH  Google Scholar 

  87. Zadeh, L.A.: A rationale for fuzzy control. Trans. ASME J. Dyn. Syst. Measur. Contr. 94 G, 3–4 (1974)

    Google Scholar 

  88. Zadeh, L.A.: The concept of linguistic variable and its application to approximate reasoning, Pts. I, II, & III. Inform. Sci. 8, 199–249; 8, 301–375; and 9, 47–80 (1975)

    MathSciNet  Google Scholar 

  89. Zadeh, L.A.: Fuzzy sets as a basis for a theory of possibilities. Fuzzy Sets & Syst. 1, 328, 1978

    MathSciNet  Google Scholar 

  90. Zadeh, L.A.: A theory of approximate reasoning. In: J.E. Hayes, D. Michi & L.I. Kulich (eds.) Machine Intelligence 9. New York: J.Wiley 1979, pp. 149–194

    Google Scholar 

  91. Zadeh, L.A.: Inference in fuzzy logic IEEE Proceedings 68, 124–131 (1980)

    Google Scholar 

  92. Zadeh, L.A.: Commonsense knowledge representation. IEEE Computer 16, 61–65 (1983)

    Article  Google Scholar 

  93. Zadeh, L.A.: Fuzzy logic IEEE Computer 21, 83–93 (1988)

    Google Scholar 

  94. Zadeh, L.A.: The calculus of if-then rules. AI Expert 7, 22–27 (1992)

    Google Scholar 

  95. Zadeh, L.A.: Fuzzy logic, neural networks and soft computing. Comm. ACM 37, 77–84 (1994)

    Article  Google Scholar 

  96. Zadeh, L.A.: Fuzzy logic = Computing with words. IEEE Trans. Fuzzy Syst. 4, 103–111 (1996)

    Article  Google Scholar 

  97. Zadeh, L.A.: The role of fuzzy logic and soft computing in intelligent control and systems analysis (Invited Plenary Lecture WAC96–1). In: M. Jamshidi (Gen.Chairman & ed.) 2nd World Automation Congress. Proceedings, Montpellier 1996

    Google Scholar 

  98. Zimmermann, H.-J.: Fuzzy sets, Decision Making and Expert Systems. Boston: Kluwer 1987

    Book  Google Scholar 

  99. Zurawski, R. & M.C. Zhou: Petri nets and industrial applications: A tutorial. IEEE Trans. Industr. Electronics 41, 567–583 (1994)

    Article  Google Scholar 

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Authors and Affiliations

  1. ASE Institute at Faculty of Electrical Engineering, St. Cyril and St.Methodius University, Karpos 2 B.B., 574, MK-91000, Skopje, Republic of Macedonia

    Georgi M. Dimirovski

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  1. Georgi M. Dimirovski
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Editors and Affiliations

  1. Faculty of Engineering, Bogaziçi University, Istanbul, TR-80815, Turkey

    Okyay Kaynak

  2. Computer Science Division, University of California at Berkeley, Berkeley, CA, 94720-1776, USA

    Lotfi A. Zadeh

  3. University of Toronto, Ontario, M5S 3G8, Canada

    Burhan Türkşen

  4. Bánki Donát Polytechnic, Népszinház u. 8, Budapest, H-1081, Hungary

    Imre J. Rudas

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Dimirovski, G.M. (1998). Fuzzified Petri-Nets and Their Application to Organising Supervisory Controller. In: Kaynak, O., Zadeh, L.A., Türkşen, B., Rudas, I.J. (eds) Computational Intelligence: Soft Computing and Fuzzy-Neuro Integration with Applications. NATO ASI Series, vol 162. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-58930-0_13

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