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Linguistic Information in Dynamical Fuzzy Systems — An Overview

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Applications of Soft Computing

Part of the book series: Advances in Soft Computing ((AINSC,volume 52))

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Summary

This paper gives an overview on the study of using linguistic information in the dynamical fuzzy systems. We introduce the Linguistic Information Feed-Back-based Dynamical Fuzzy System (LIFBDFS) and Linguistic Information Feed-Forward-based Dynamical Fuzzy System (LIFFDFS), in which the past fuzzy inference output represented by a membership function is fed back and forward, respectively. Their principles, structures, and learning algorithms are also presented. Both the LIFBDFS and LIFFDFS can overcome the common static mapping drawback of conventional fuzzy systems. They have the distinguished advantage of inherent dynamics, and are, therefore, well suited for handling temporal problems, such as process modeling and control. Our survey paper provides a general guideline for interested readers to choose, design, and apply these linguistic information feed-back- and feed-forward-based dynamical fuzzy systems in engineering.

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References

  1. Pedrycz, W.: Fuzzy sets in pattern recognition: Methodology and methods. Pattern Recognition 23(1), 121–146 (1990)

    Article  MathSciNet  Google Scholar 

  2. Lee, C.C.: Fuzzy logic in control systems: Fuzzy logic controller, Parts I and II. IEEE Transactions on Systems, Man, and Cybernetics 20(2), 404–435 (1990)

    Article  MATH  Google Scholar 

  3. Kwong, W.A., Passino, K.M., Laukonen, E.G., Yurkovich, S.: Expert supervision of fuzzy learning systems for fault tolerant aircraft control. Proc. IEEE 83(3), 466–483 (1995)

    Article  Google Scholar 

  4. Gao, X.Z., Ovaska, S.J.: Dynamical fuzzy systems with linguistic information feedback. In: Melo-Pinto, P., Teodorescu, H.-N., Fukuda, T. (eds.) Systematic Organization of Information in Fuzzy Systems. IOS Press, Amsterdam (2003)

    Google Scholar 

  5. Gao, X.Z., Ovaska, S.J.: Linguistic information feed-forward-based dynamical fuzzy systems. IEEE Transactions on Systems, Man, and Cybernetics, Part C 36(4), 453–463 (2006)

    Article  Google Scholar 

  6. Zhang, J., Morris, A.J.: Recurrent neuro-fuzzy networks for nonlinear process modeling. IEEE Transactions on Neural Networks 10(2), 313–326 (1999)

    Article  Google Scholar 

  7. Tang, K.S., Man, K.F., Kwong, S., He, Q.: Genetic algorithms and their applications. IEEE Signal Processing 13(6), 22–37 (1996)

    Article  Google Scholar 

  8. Gao, X.Z., Ovaska, S.J., Wang, X.: Learning algorithm for Linguistic Information Feedback-based Dynamical Fuzzy Systems (LIFDFS). In: Proc. IEEE International Conference on Systems, Man, and Cybernetics, The Hague, The Netherlands, October 2004, pp. 2278–2285 (2004)

    Google Scholar 

  9. Lin, C.-T., Lu, Y.-C.: A neural fuzzy system with linguistic teaching signals. IEEE Transactions on Fuzzy Systems 3(2), 169–188 (1995)

    Article  Google Scholar 

  10. Werbos, P.J.: Backpropagation through time: What it does and how to do it. Proc. IEEE 78(10), 1550–1560 (1990)

    Article  Google Scholar 

  11. Haykin, S.: Neural Networks: A Comprehensive Foundation, 2nd edn. Prentice-Hall, Upper Saddle River (1999)

    MATH  Google Scholar 

  12. Gao, X.Z., Ovaska, S.J., Wang, X.: A simplified linguistic information feedback-based dynamical fuzzy system with learning algorithm — Part I: Theory. In: Proc. IEEE Mid-Summer Workshop on Soft Computing in Industrial Applications, Espoo, Finland, June 2005, pp. 44–50 (2005)

    Google Scholar 

  13. Gao, X.Z., Ovaska, S.J., Wang, X.: A simplified linguistic information feedback-based dynamical fuzzy system with learning algorithm — Part II: Evaluation. In: Proc. IEEE Mid-Summer Workshop on Soft Computing in Industrial Applications, Espoo, Finland, June 2005, pp. 51–56 (2005)

    Google Scholar 

  14. Wang, L.-X.: A Course in Fuzzy Systems and Control. Prentice-Hall, Upper Saddle River (1997)

    MATH  Google Scholar 

  15. Box, G.E.P., Jenkins, G.M.: Time Series Analysis: Forecasting and Control, 2nd edn. Holden-Day, San Francisco (1976)

    MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, Helsinki University of Technology, Otakaari 5 A, FI-02150, Espoo, Finland

    Xiao-Zhi Gao & Xiaolei Wang

  2. Department of Electrical and Computer Engineering, Utah State University, 4120 Old Main Hill, Logan, UT 84322-4120, U.S.A.

    Seppo Ovaska

Authors
  1. Xiao-Zhi Gao
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  2. Seppo Ovaska
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  3. Xiaolei Wang
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Editor information

Editors and Affiliations

  1. Senior Lecturer in Integrated Transport Centre for Transport & Society Faculty of the Built Environment, University of the West of England, Frenchay Campus Coldharbour Lane, BS16 1QY, Bristol, UK

    Erel Avineri

  2. Kyushu Institute of Technology, Dept. Artificial Intelligence, 680-4 Kawazu Izuka-Shi, 820-8502, Fukuoka, Japan

    Mario Köppen

  3. MOSAIC Research Group Department of Computing, University of Bradford, BD7 1DP, Bradford, UK

    Keshav Dahal

  4. Centre for Transport & Society Faculty of the Built Environment, University of the West of England, Frenchay Campus Coldharbour Lane, BS16 1QY, Bristol, UK

    Yos Sunitiyoso

  5. Professor of Decision Engineering and Head of Decision Engineering Centre Manufacturing Department, Cranfield University, MK43 OAL, Bedford, UK

    Rajkumar Roy

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© 2009 Springer-Verlag Berlin Heidelberg

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Gao, XZ., Ovaska, S., Wang, X. (2009). Linguistic Information in Dynamical Fuzzy Systems — An Overview. In: Avineri, E., Köppen, M., Dahal, K., Sunitiyoso, Y., Roy, R. (eds) Applications of Soft Computing. Advances in Soft Computing, vol 52. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88079-0_1

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  • DOI: https://doi.org/10.1007/978-3-540-88079-0_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-88078-3

  • Online ISBN: 978-3-540-88079-0

  • eBook Packages: EngineeringEngineering (R0)

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