NDLI: A Novel Neural Network Model of Hysteresis Nonlinearities

Content Provider	IEEE Xplore Digital Library
Author	Zhao Tong Shulin Sui Changhe Du
Copyright Year	2006
Description	Author affiliation: Dept. of Autom., Qingdao Univ. of Sci. & Technol. (Zhao Tong; Shulin Sui)
Abstract	A novel and simple modeling method of hysteresis nonlinearities is proposed. Through analyzing the principle of the classical Preisach model, we find some characteristics and rules of motion point, i.e. trajectory of output to input, and believe that hysteresis curve, with analytic geometry method, can be constructed. The hysteresis curves from the constructed models, wonderfully match with a class of simulation hysteresis model, which consist of many backlash models. Though the hysteresis model is only a special class, when its output is used as one of input signals of neural networks, the neural networks model can approximate other classes of hysteresis curve. Three examples, including one simulation data set and two measured experimentation data sets, are implemented. The results indicate that the proposed method is successful and simple
Starting Page	84
Ending Page	89
File Size	240958
Page Count	6
File Format	PDF
ISBN	0769525288
DOI	10.1109/ISDA.2006.72
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-10-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Deformable models Solid modeling Automation modeling Artificial neural networks Open loop systems Magnetic hysteresis neural network hysteresis Geometry analytic geometry Neural networks Control system synthesis Mathematical model
Content Type	Text
Resource Type	Article

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