Classification of Fuzzy Petri Nets, and Their Applications
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Classification of Fuzzy Petri Nets, and Their Applications

Authors: M.H.Aziz, Erik L.J.Bohez, Manukid Parnichkun, Chanchal Saha

Abstract:

Petri Net (PN) has proven to be effective graphical, mathematical, simulation, and control tool for Discrete Event Systems (DES). But, with the growth in the complexity of modern industrial, and communication systems, PN found themselves inadequate to address the problems of uncertainty, and imprecision in data. This gave rise to amalgamation of Fuzzy logic with Petri nets and a new tool emerged with the name of Fuzzy Petri Nets (FPN). Although there had been a lot of research done on FPN and a number of their applications have been anticipated, but their basic types and structure are still ambiguous. Therefore, in this research, an effort is made to categorize FPN according to their structure and algorithms Further, literature review of the applications of FPN in the light of their classifications has been done.

Keywords: Discrete event systems, Fuzzy logic, Fuzzy Petri nets, and Petri nets.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1063110

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References:


[1] Richard Zurawski, and MengChu Zhou, "Petri nets and industrial applications: A tutorial," IEEE. Trans. Industrial Electronics, vol. 41, no. 6, pp. 567-583, Dec. 1994.
[2] George J. Klir, Ute H. St. Clair, and Bo Yuan, Fuzzy set theory; foundations and applications. London: Prentice Hall, 1997.
[3] Yung-Hsiang Cheng, and Li-An Yang, "A Fuzzy Petri nets approach for railway traffic control in case of abnormality: Evidence from Taiwan railway system," Expert Systems with Applications, vol. 36, pp. 8040¬8048, 2009.
[4] S. M. Chen, J. S. Ke, and J. F. Chang, "Knowledge representation using fuzzy Petri nets," IEEE Trans. Knowledge and Data Engineering, vol. 2, no. 3, pp. 311-319, SEP 1990.
[5] J.-S. R. Jang, Ch.-T. Sun, and E. Muzutani, Neuro-Fuzzy and Soft Computing-A Computational Approach to Learning and Machine Intelligence. London: Prentice Hall, 1997.
[6] J. Cardoso, R. Valette, and D. Dubois, "Fuzzy Petri net: An overview," in Proc. 13th IFAC World Congr., 1996, pp. 443-448.
[7] Alexander Fay, "A fuzzy knowledge-based system for railway traffic control," Engng. Applic. Artif. Intell., vol. 13, no. 6, pp. 719-729, Dec. 2000.
[8] Hong-Tzer Yang, and Chao-Ming Huanh, "Distribution system service restoration using fuzzy Petri net models," Electric Power and Energy System, vol. 24, no. 5, pp. 3 395-403, Jun. 2002.
[9] Walter Eversheim, and Thomas Hack, "Managing multiple product variants in assembly control with a Fuzzy Petri net approach," Annals of the ClRP, vol. 45, no. 1, p. 45, 1996.
[10] Rajiv Kumar Sharma, Dinesh Kumar, and Pradeep Kumar, "Predicting uncertain behavior of industrial system using FM-A practical case," Applied Soft Computing, vol. 8, no. 1, pp. 96-109, Jan. 2008.
[11] Y. Ting, W.B. Lu, C.H. Chen, and G.K. Wang, "A fuzzy reasoning design for fault detection and diagnosis of a computer-controlled system," Engng. Applic. Artif Intell., vol. 21, no. 2, pp. 157-170, Mar. 2008.
[12] Zouhua Dinga, Horst Bunkeb, Mti Schneiderd, and Abraham Kandela, " Fuzzy timed Petri net definitions, properties, and applications," Mathematical and Computer Modelling, vol. 41, no. 2-3, pp. 345-360, Feb. 2005.
[13] Zouhua Dinga, Horst Bunkeb, Oscar Kipersztokc, Mti Schneiderd, and Abraham Kandela, "Fuzzy timed Petri nets- analysis and implementation," Mathematical and Computer Modelling vol. 43, no. 3¬4, pp. 385-400, Feb. 2006.
[14] Witold Pedrycz, and Heloisa Camargo, "Fuzzy timed Petri nets," Fuzzy Sets and Systems vol. 140, no. 2, pp. 301-330, Dec. 2003.
[15] Jorge C.A. de Figueiredo, and Angelo Perkusich, "Faults and timing analysis in realtime distributed systems: A fuzzy time Petri-net-based approach," Fuzzy Sets and Systems vol. 83, no. 2, pp. 143-168, Oct. 1996.
[16] D. Ben-Arieha, Rajeev Ranjan Kumarb, and M.K. Tiwari, "Analysis of assembly operations' difficulty using enhanced expert high-level colored fuzzy Petri net model," Robotics and Computer-Integrated Manufacturing vol. 20, no. 5, pp. 385-403, Oct. 2004.
[17] Seung Jun Lee, and Poong Hyun Seong, "Development of automated operating procedure system using Fuzzy colored Petri nets for nuclear power plants," Annals of Nuclear Energy, vol. 31, no. 8, pp. 849-869, May 2004.
[18] M. S. Ouali, D. Ait-Kadi, and N. Rezg, "Fault diagnosis model based on Petri net with fuzzy colors," Computers and Industrial Engineering, vol. 37, no. 1-2, pp. 173-176, Oct. 1999.
[19] Grantham K. H. Pang, Raymond Tang, and Stephen S. Woo, "A Process-control and diagnostic tool based on continuous Fuzzy Petri nets," Engng. Applic. Artif. Intell., vol. 8, no. 6, pp. 643-650, Dec. 1995.
[20] X. Li, and F. Lara-Rosano, "Adaptive fuzzy Petri nets for dynamic knowledge representation and inference," Expert Systems with Applications, vol. 19, no. 3, pp. 235-241, Oct. 2000.
[21] Martin T. Hagan, Howard B. Demuth and Mark Beale, Neural network design. Boston: PWS publishing Co., 1996.
[22] Yueh-Min Huang, Juei-Nan Chen, Tien-Chi Huang, Yu-Lin Jeng, and Yen-Hung Kuo, "Standardized course generation process using dynamic Fuzzy Petri nets," Expert Systems with Applications, vol. 34, no. 1, pp. 72-86, Jan. 2008.
[23] Amit Konar, and Uday K. Chakraborty, "Reasoning and unsupervised learning in a Fuzzy cognitive map," Information Sciences, vol. 170, no. 2-4, pp. 419-441, Feb. 2005.
[24] Witold Pedrycz , "Generalized Fuzzy Petri nets as pattern classifiers," Pattern Recognition Letters, vol. 20, no. 14, pp. 1489-1498, Dec. 1999.
[25] Amit Konar, Uday K. Chakraborty, and Paul P. Wang, "Supervised learning on a Fuzzy Petri net," Information Sciences vol. 172, no. 3-4, pp. 397-416, Jun. 2005.
[26] Man Leung Wong, "A flexible knowledge discovery system using genetic programming and logic grammars," Decision Support Systems vol. 31, no. 4, pp. 405-428, Oct. 2001.
[27] C.A. Gracios, Marin E. Vargas Soto, and A. Diaz Sanchez, "Describing an IMS by a FNRTPN definition: a VHDL approach," Robotics and Computer-Integrated Manufacturing vol. 21, no. 3, pp. 241-247, Jun. 2005.
[28] J.J. Henry, J. L. Farges, and J. L. Gallego, "Neuro-Fuzzy techniques for traffic control," Control Engineering Practice vol. 6, no. 6, pp. 755-761, Jun. 1998.
[29] Erik L. J. Bohez, "A new generic timed Petri net model for design and performance analysis of a dual Kanban FMS," int. j. production research, vol. 42, no. 4, pp. 719-740, 2004.