skip to main content
10.5555/1717561.1717715guideproceedingsArticle/Chapter ViewAbstractPublication PagesConference Proceedingsacm-pubtype
Article

An extended fuzzy logic system for uncertainty modelling

Published: 20 August 2009 Publication History

Abstract

An extended fuzzy logic system (EFLS) based on interval fuzzy membership functions is proposed for covering more uncertainty in practical applications. With the degree of uncertainty in fuzzy membership functions, interval fuzzy membership functions are self-generated to include uncertainties which occur from understanding linguistic knowledge and fuzzy rules in fuzzy methods. A novel adaptive strategy is designed to self-tune the interval fuzzy membership functions and to deduce the crisp outputs with feedback structure. An inverse kinematics modelling study based on a two-joint robotic arm has demonstrated that proposed EFLS outperforms conventional fuzzy methods.

References

[1]
L.A. Zadeh. Fuzzy sets. Information and Control, 8(3):338-353, 1965.
[2]
G. Klir and T. Folger. Fuzzy sets, uncertainty, and information. Prentice-Hall, Inc. Upper Saddle River, NJ, USA, 1987.
[3]
J Mendel and R. John. Type-2 fuzzy sets made simple. Fuzzy Systems, IEEE Transactions on, 10(2):117-127, 2002.
[4]
T. Ross. Fuzzy logic with engineering applications. Wiley, 2004.
[5]
H. Hagras. A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots. Fuzzy Systems, IEEE Transactions on, 12(4):524-539, 2004.
[6]
Z. Liu and H. Li. A probabilistic fuzzy logic system for modeling and control. Fuzzy Systems, IEEE Transactions on, 13(6):848-859, 2005.
[7]
N. Karnik and J. Liang. Type-2 fuzzy logic systems. Fuzzy Systems, IEEE Transactions on, 7(6):643-658, 1999.
[8]
Q. Liang and J. Mendel. Interval type-2 fuzzy logic systems: theory and design. Fuzzy Systems, IEEE Transactions on, 8(5):535-550, 2000.
[9]
J. Castro, O. Castillo, and P. Melin. Intelligent control using an interval type-2 fuzzy neural network with a hybrid learning algorithm. In FUZZ-IEEE 2008, pages 893-900, Hong Kong, June 2008.
[10]
H. Hagras. Developing a type-2 flc through embedded type-1 flcs. In FUZZ-IEEE 2008, pages 148-155, Hong Kong, June 2008.
[11]
M. Nie and W. Tan. Towards an efficient type-reduction method for interval type-2 fuzzy logic systems. In FUZZ-IEEE 2008, pages 1425-1432, Hong Kong, June 2008.
[12]
J. Cao, H. Liu, P. Li, and D. Brown. Adaptive fuzzy logic controller for vehicle active suspensions with interval type-2 fuzzy membership functions. In FUZZ-IEEE 2008, pages 83-89, Hong Kong, June 2008.
[13]
Z. Liu and H. Li. A probabilistic fuzzy logic system for uncertainty modeling. In Systems, Man and Cybernetics, 2005 IEEE International Conference on, volume 4, 2005.
[14]
P. Baranyi, L. Koczy, and T. Gedeon. A generalized concept for fuzzy rule interpolation. Fuzzy Systems, IEEE Transactions on, 12(6):820-837, 2004.
[15]
Z. Huang and Q. Shen. Fuzzy interpolative reasoning via scale and move transformations. Fuzzy Systems, IEEE Transactions on, 14(2):340, 2006.
[16]
L. Lee and S. Chen. Fuzzy interpolative reasoning for sparse fuzzy rule-based systems based on the ranking values of fuzzy sets. Expert Systems With Applications, 35(3):850-864, 2008.
[17]
J. Gan, E. Oyama, E. Rosales, and H. Hu. A complete analytical solution to the inverse kinematics of the Pioneer 2 robotic arm. Robotica, 23(01):123-129, 2005.
[18]
H. Liu, G. Coghill, and D. Brown. Qualitative kinematics of planar robots: intelligent connection. International Journal of Approximate Reasoning, 46(3):525-541, 2007.
[19]
H. Liu, D. Brown, and G. Coghill. Fuzzy qualitative robot kinematics. Fuzzy Systems, IEEE Transactions on, 16(3):808-822, 2008.
[20]
H. Liu. A fuzzy qualitative framework for connecting robot qualitative and quantitative representations. Fuzzy Systems, IEEE Transactions on, 16(6):1522-1530, 2008.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image Guide Proceedings
FUZZ-IEEE'09: Proceedings of the 18th international conference on Fuzzy Systems
August 2009
2186 pages
ISBN:9781424435968

Publisher

IEEE Press

Publication History

Published: 20 August 2009

Qualifiers

  • Article

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 0
    Total Downloads
  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 27 Dec 2024

Other Metrics

Citations

View Options

View options

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media