It has been known that it is difficult to establish a fuzzy logic model with effective fuzzy rules and the associated membership functions. Neural network with its learning capability has been incorporated to make the fuzzy model more adaptive and effective. A self-organized neuro-fuzzy model by integrating the Mamdani fuzzy model and the backpropagation neural network is developed in this paper for system identification. The five-layer network adaptively adjusts the membership functions and dynamically optimizes the fuzzy rules. A benchmark test is applied to validate the model accuracy in nonlinear system identification. Experimental verifications on the dynamics of a composite smart structure and on an acoustics system also demonstrate that the neuro-fuzzy model is superior to the neural network and to an adaptive filter in system identification. The model can be established systematically and is shown to be effective in engineering applications.
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e-mail: smyang@mail.ncku.edu.tw
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August 2007
Technical Papers
Development of a Self-Organized Neuro-Fuzzy Model for System Identification
S. M. Yang,
S. M. Yang
Professor
Institute of Aeronautics and Astronautics,
e-mail: smyang@mail.ncku.edu.tw
National Cheng Kung University
, Taiwan, ROC
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C. J. Chen,
C. J. Chen
Graduate Student
Institute of Aeronautics and Astronautics,
National Cheng Kung University
, Taiwan, ROC
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Y. Y. Chang,
Y. Y. Chang
Graduate Student
Institute of Aeronautics and Astronautics,
National Cheng Kung University
, Taiwan, ROC
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Y. Z. Tung
Y. Z. Tung
Graduate Student
Institute of Aeronautics and Astronautics,
National Cheng Kung University
, Taiwan, ROC
Search for other works by this author on:
S. M. Yang
Professor
Institute of Aeronautics and Astronautics,
National Cheng Kung University
, Taiwan, ROCe-mail: smyang@mail.ncku.edu.tw
C. J. Chen
Graduate Student
Institute of Aeronautics and Astronautics,
National Cheng Kung University
, Taiwan, ROC
Y. Y. Chang
Graduate Student
Institute of Aeronautics and Astronautics,
National Cheng Kung University
, Taiwan, ROC
Y. Z. Tung
Graduate Student
Institute of Aeronautics and Astronautics,
National Cheng Kung University
, Taiwan, ROCJ. Vib. Acoust. Aug 2007, 129(4): 507-513 (7 pages)
Published Online: December 14, 2006
Article history
Received:
December 16, 2005
Revised:
December 14, 2006
Citation
Yang, S. M., Chen, C. J., Chang, Y. Y., and Tung, Y. Z. (December 14, 2006). "Development of a Self-Organized Neuro-Fuzzy Model for System Identification." ASME. J. Vib. Acoust. August 2007; 129(4): 507–513. https://doi.org/10.1115/1.2731417
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