Soft Computing and Fractal Theory for Intelligent Manufacturing

• Autorzy: Castillo O. , Melin P.
• Języki publikacji: EN

Abstrakty

EN

We describe in this paper the combination of soft computing techniques and fractal theory for achieving intelligent manufacturing. Soft computing techniques can be used to develop hybrid intelligent systems. Fractal theory can be used to analyze the geometrical complexity of natural and artificial objects. The careful combination of soft computing and fractal theory can provide us with a good mix of intelligent techniques and fractal mathematical tools, which can help in achieving automation of manufacturing processes. We consider in this paper several manufacturing and automation problems that are efficiently solved with the proposed approach.

Słowa kluczowe

EN

fuzzy logic; fractal theory; neural network

• Wydawca: Łukasiewicz Industrial Research Institute for Automation and Measurements PIAP
• Czasopismo: Journal of Automation Mobile Robotics and Intelligent Systems
• Rocznik: 2007
• Tom: Vol. 1, No. 1
• Strony: 41--47
• Opis fizyczny: Bibliogr. 47 poz., rys.

Twórcy

autor

Castillo O.

autor

Melin P.

• Professor of the Computer Science Department of Tijuana Institute of Technology, Tijuana, Mexico.,

Bibliografia

• [1] Betin F., Pinchon D. & Capolino G. A., "Fuzzy logic applied to speed control of a motor drive", IEEE Transaction of Industrial Electronics, 2000, vol. 47, pp. 610-622.
• [2] Bezdek J.C.,Pattern Recognition with Fuzzy Objective Function Algorithms, Plenum Press, New York, 1981.
• [3] Bode H., Brodd R.J. & Kordesch K.V.,Lead-Acid Batteries ,John Wiley & Sons, 1977.
• [4] Castillo O. & Melin P., "Developing a New Method for the Identification of Microorganisms for the Food Industry using the Fractal Dimension",Journal of Fractals , World Scientific, 1994, vol. 2, no. 3, pp. 457-460.
• [5] Castillo O. & Melin P., "An Intelligent System for Financial Time Series Prediction Combining Dynamical Systems Theory, Fractal Theory and Statistical Methods", Proceedings of CIFER'95, IEEE Computer Society Press, 1995, pp.151-155.
• [6] Castillo O. & Melin P., "Mathematical Modelling and Simulation of Robotic Dynamic Systems using Fuzzy Logic Techniques and Fractal Theory", Proceedings of IMACS World Congress'97 , Wissenschaft & Technik Verlag, 1997, vol. 5, pp.343-348.
• [7] Castillo O. & Melin P., "A New Fuzzy-Fractal-Genetic Method for Automated Mathematical Modelling and Simulation of Robotic Dynamic Systems",Proceedings of World Congress on Computational Intelligence FUZZ'98 , IEEE Computer Society Press, 1998, vol. 2, pp. 1182-1187.
• [8] Castillo O. & Melin P., "Automated Mathematical Modelling, Simulation and Behavior Identification of Robotic Dynamic Systems using a new Fuzzy-Fractal-Genetic Approach", Journal of Robotics and Autonomous Systems 1999, vol. 28, no. 1, pp. 19-30.
• [9] Castillo O. & Melin P., "A New Method for Fuzzy Estimation of the Fractal Dimension and its Applications to Time Series Analysis and Pattern Recognition",Proceedings of NAFIPS'2000, Atlanta, GA, USA, 2000, pp. 451-455.
• [10] Castillo O. & Melin P., "Modelling, Simulation and Behavior Identification of Non-Linear Dynamical Systems with a New Fuzzy-Fractal Genetic Approach",Edited Book in the Series of Advances in Fuzzy Systems edited by B. Bouchon, R. Yager, & L. A. Zadeh, World Scientific, 2000, pp. 95-106.
• [11] Castillo O. & Melin P., "Soft Computing for Control of Non-Linear Dynamical Systems", Springer-Verlag, 2001,Heidelberg, Germany.
• [12] Castillo O. & Melin P., "A New Theory of Fuzzy Chaos and its Application for Simulation of Robotic Dynamic Systems", Proceedings of the 6th Joint Conference on Information Sciences, 2002, Durham, North Carolina, USA, pp. 149-152.
• [13] Castillo O. and Melin P.,Soft Computing and Fractal Theory for Intelligent Manufacturing, Springer-Verlag, 2003, Heidelberg, Germany.
• [14] Chiang L.H., Russell E.L., & Braatz R.D.,"Fault Detection and Diagnosis in Industrial Systems", Springer-Verlag,2000, Heidelberg, Germany.
• [15] Denker J. S., "Neural Networks for Computation", In: J.S.Denker, editor, AIP Conference Proceedings, 1986, American Institute of Physics p. 151.
• [16] Devaney R., An Introduction to Chaotic Dynamical Systems,Addison Wesley Publishing, 1989.
• [17] Dickason V., The Loudspeaker Cookbook, McGraw Hill, 1997.
• [18] Du R., "Engineering Monitoring and Diagnosis",Edited Book Industrial and Manufacturing Systems, Academic Press, 1998, San Diego, California, USA, pp. 119-144.
• [19] Du R., Elbestawi M. A., & Wu S.M., "Automated Monitoring of Manufacturing Processes", Transactions ASME J. Eng.Ind, 1993, pp. 245-252.
• [20] Goldberg D.E., Genetic Algorithms in Search, Optimization and Machine Learning, Addison Wesley Publishing, 1989.
• [21] Hehner N. & Orsino J.A., Storage Battery Manufacturing Manual III, Independent Battery Manufacturers Association, 1985.
• [22] Holland J. H., Adaptation in Natural and Artificial Systems, University of Michigan Press, 1975.
• [23] Hopfield J. J., "Neural Networks and Physical Systems with Emergent Collective Computational Abilities",Proceedings of the National Academy of Science, USA, 1982, pp. 2554-2558.
• [24] Jang J.-S. R., Sun C.-T., & Mizutani, E., "Neurofuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence", Prentice-Hall, 1997.
• [25] Karnik N.N & Mendel J.M., An Introduction to Type-2 Fuzzy Logic Systems, Technical Report, University of Southern California, 1998.
• [26] Kohonen T., "Improved Version of Learning Vector Quantization",Proceedings of the IJCNN'90, San Diego, CA, USA, 1990, vol. 1 pp. 545-550.
• [27] Kosko B.,"Neural Networks and Fuzzy Systems: A Dynamical Systems Approach to Machine Intelligence", Prentice-Hall, 1992.
• [28] Kosko B. , Fuzzy Engineering, Prentice-Hall, 1997.
• [29] Loctite Co. (1999).Speaker Assembly Adhesives Guide.
• [30] Mamdani E. H., "Application of fuzzy algorithms for control of a simple dynamic plant",Proceedings of IEEE, 1974, vol. 121, pp. 1585-1588.
• [31] Man K. F., Tang K.S. & Kwong S.,Genetic Algorithms, Springer-Verlag, 1999.
• [32] Mandelbrot B.,The Fractal Geometry of Nature, W. H. Freeman and Company, 1987.
• [33] Mandelbrot B., Fractals and Scaling in Finance, Springer-Verlag, 1997, Heidelberg, Germany.
• [33] Margaliot M. & Langholz G., New Approaches to Fuzzy Modeling and Control , World Scientific Press, 2000, Singapore.
• [34] Melin P. and Castillo O., "A new approach for quality control of sound speakers combining type-2 fuzzy logic and fractal theory", In:2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE'02 Proceedings, Part 2, pages 825 -830.
• [35] Mendel J.,Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions, Prentice-Hall, 2001,New Jersey, USA.
• [36] Michalewicz Z.,Genetic Algorithms + Data Structures = Evolution program, 3rd Edition, Springer-Verlag, 1996.
• [37] Ogorzalek M. J., "Taming Chaos-Part II: Control",IEEE Transactions on Circuit Systems, 1993, vol. 40, pp. 700-721.
• [38] Pyragas K., "Continuous control of chaos by selfcontrolling feedback",Physical Letters, 1992, pp. 421-428.
• [39] Semmes S.,Some Novel Types of Fractal Geometry , Oxford University Press, England, 2000.
• [40] Sepulveda R., Castillo O., Montiel O. and Lopez M., "Analysis of Fuzzy Control System for the Process of Forming Batteries", Proceedings of ISRA'98, Coahuila, Mexico, 1998, pp. 203-210.
• [41] Sugeno M. & Kang G. T., Structure Identification of Fuzzy Model,Journal of Fuzzy Sets and Systems , 1988, vol. 28, pp.15-33.
• [42] Wagenknecht M. & Hartmann K., "Application of Fuzzy Sets of Type 2 to the solution of Fuzzy Equation Systems",Fuzzy Sets and Systems, 1988, vol. 25, pp. 183-190.
• [43] Werbs P. J., "An Overview of Neural Networks for Control", IEEE Control Systems Magazine, 1991, vol. 11, pp. 40-41.
• [44] Yager R.R., "Fuzzy Subsets of Type II in Decisions",Journal of Cybernetics, 1980, vol. 10, pp. 137-159.
• [45] Yager R. R. & Filev D.P., "Generation of Fuzzy Rules by Mountain Clustering",Journal of Intelligent and Fuzzy Systems, 1994, vol. 2, no. 3, pp. 209-219.
• [46] Zadeh L.A., "Fuzzy Sets",Journal of Information and Control, 1965, vol. 8, pp. 338-353.
• [47] Zadeh L.A.,"The Concept of a Linguistic Variable and its Application to Approximate Reasoning 1",Journal of Information Sciences, 1975, vol. 8, pp. 199-249.