DocumentCode
2394303
Title
EHM Based Neural Model for Hysteresis
Author
Ma, Lianwei ; Tan, Yonghong
Author_Institution
Dept. of Autom., Shanghai Jiaotong Univ.
fYear
0
fDate
0-0 0
Firstpage
194
Lastpage
197
Abstract
This paper proposes a neural model for hysteresis. A method of continuous transformation is used to construct an elementary hysteresis model (EHM), which implements a one-to-one mapping between the input space and the output space of the hysteresis. The output of the EHM is used as one of the input signals of the neural network (NN) to approximate the behavior of hysteresis. A parabolic factor is introduced to improve the modeling performance for the major and minor loops of the hysteresis
Keywords
hysteresis; neural nets; transforms; EHM based neural model; continuous transformation; elementary hysteresis model; neural network; one-to-one mapping; parabolic factor; Degradation; Intelligent systems; Magnetic hysteresis; Magnetic levitation; Neural networks; Neurons; Oscillators; Piezoelectric actuators; System identification; System performance;
fLanguage
English
Publisher
ieee
Conference_Titel
Networking, Sensing and Control, 2006. ICNSC '06. Proceedings of the 2006 IEEE International Conference on
Conference_Location
Ft. Lauderdale, FL
Print_ISBN
1-4244-0065-1
Type
conf
DOI
10.1109/ICNSC.2006.1673141
Filename
1673141
Link To Document