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Vol: 51(65) No: 1 / March 2006 Fuzzy Logic Control Problems Simulation Based on Parametrizied Operators Marta Takacs Budapest Tech, John von Neumann Faculty of Informatics, Institute of Intelligent Engineering Systems, Bécsi út 96/b, 1034 Budapest, Hungary, phone: (+361) 666-5544, e-mail: takacs.marta@nik.bmf.hu Sandor Szenasi Budapest Tech, John von Neumann Faculty of Informatics, Institute of Intelligent Engineering Systems, Bécsi út 96/b, 1034 Budapest, Hungary, phone: (+361) 666-5544, e-mail: szenasi.sandor@nik.bmf.hu Agnes Szeghegyi Budapest Tech, Keleti Karoly Faculty of Economics, NépszÃnház utca 8., 1081 Budapest, Hungary, phone: (+361) 210-1450, e-mail: szeghegyi.agnes@kgk.bmf.hu Keywords: FLC, distance based operators, approximate reasoning. Abstract The practical realization of the Fuzzy Logic Controler usually depends on the application. Using the parameter-depended group of fuzzy operators like distance based operators in the approximate reasoning process the FLC components can be adapted to achieve better results. The environment, applied by simulation, supports the choosing of suitable fuzzy operators and their parameters. The simulation results are analysed, depending on the efficiency of the operator choice in approximate reasoning model. References [1] B. De Baets, H. De Meyer and H. Naessens, “On rational cardinality-based inclusion measuresâ€, Fuzzy Sets and Systems, vol. 128 pp. 168 – 183, 2002. [2] B. De Baets, H. De Meyer and H. Naessens, “A class of rational cardinality-based similarity measuresâ€, Journal of Computational and Applied Mathematics, vol. 132, pp. 51 – 69, 2001. [3] Dimiter Driankov, H. Hellendron and M. Reinfrank, An Introduction to Fuzzy Control, Springer-Verlag Berlin-Heidelberg-NewYork, 1996. [4] J. Fodor and M. Rubens, Fuzzy Preference Modelling and Multicriteria Decision Support. Kluwer Academic Pub., 1994. [5] J. C. Fodor, B.De Baets and T. Calvo, “Structure of uninorms with given continuous underlying t-norms and t-conormsâ€, Proc. 24th Linz Seminar on Fuzzy Sets, 2003. [6] I. J. Rudas, “New approach to information aggregationâ€, Journal of Information and Organizational Sciences, vol. 24, no.2, pp. 163 – 176, 2000. [7] B. de Baets and J. Fodor, “Residual operators of uninormsâ€, Soft Computing, vol. 3, pp. 89 – 100, 1999. [8] M. Takacs, Approximate Reasoning in Fuzzy Systems Based On Pseudo-Analysis, Phd Thesis, Univ. of Novi Sad, 2004. [9] L. Horváth and I. J. Rudas, Modeling and Problem Solving Techniques for Engineers, Elsevier Academic Press, USA, 2004. [10] L. A. Zadeh, “A theory of approximate reasoningâ€, In Hayes, J., and editors, Machine Intelligence, vol. 9, Halstead Press, New York, pp. 149 – 194, 1979. [11] E. H. Mamdani and S. Assilian, „An experiment in linguistic syntesis with a fuzzy logic controllerâ€, International Journal Man-Machine Stud., vol. 7, pp. 1 – 13, 1975. [12] M. Takacs and Zs. Baky, “Parameter-based program-interface for a FLC simulation systemâ€, Proceedings of the SACI 2005 Symposium, Timisoara, 2005. |