Development of a rule selection mechanism by using neuro-fuzzy methodology for structural vibration suppression

Authors:
Chuen-Jyh Chen;Shih-Ming Yang;Chu-Yun Chen
Affiliations:
Department of Air Transportation Management, Aletheia University, Tainan City, Taiwan, R.O.C.;Department of Aeronautics and Astronautics, National Cheng Kung University, Tainan City, Taiwan, R.O.C.;Department of Aeronautics and Astronautics, National Cheng Kung University, Tainan City, Taiwan, R.O.C.
Venue:
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Year:
2013

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Abstract

The development of neuro-fuzzy systems by integrating neural networks and fuzzy systems is desired because such systems can adjust fuzzy membership functions and produce fuzzy inference rules by case-learning without the need for experts or experiments. It has been applied to various fields, but there has been no detailed study of the various neuro-fuzzy models applicable to rule generation. In this paper, an experimentally verified five-layer and three-phase network is presented, which shows the effectiveness with which the neuro-fuzzy system automatically determines membership functions and selects activation fuzzy rules using both system identification and vibration control examples in engineering applications.