A New Method to Identify the Preisach Distribution Function of Hysteresis


Article Preview

In this paper, a new method which combines the least square method with Tree-Structured fuzzy inference system is presented to approximate the Preisach distribution function. Firstly, by devising the input sequence and measure the output, discrete Preisach measure can be identified by the use of the least squares method. Then, the Preisach function can be obtained with Tree-Structured fuzzy inference system without any special smoothing means. So, this new method is not sensitive to noise, and is a universal approximator of the Preisach function. It collect the merit and overcome the deficiency of the existing methods.



Materials Science Forum (Volumes 475-479)

Main Theme:

Edited by:

Z.Y. Zhong, H. Saka, T.H. Kim, E.A. Holm, Y.F. Han and X.S. Xie




F. Li et al., "A New Method to Identify the Preisach Distribution Function of Hysteresis", Materials Science Forum, Vols. 475-479, pp. 2107-2110, 2005

Online since:

January 2005




[1] X. B. Tan and J. S. Baras: Modeling and Control of a Magnetostrictive Actuator. Proceedings of the 41th IEEE Conference on Decision and Control, Las Vegas, Nevada USA (2002), pp.866-872.

[2] C. Natale, F. Velardi, and C. Visone: Modelling and compensation of hysteresis for magnetostrictive actuators. In Proceedings of IEEE/ASME International Conference on Advanced Intelligent Mechatronics (2001), pp.744-749.

DOI: https://doi.org/10.1109/aim.2001.936759

[3] Jianqin Mao, Jiangang Zhang, Yufang Yue, Haishan Ding: Adaptive-Tree-Structure-Based Fuzzy Inference System. IEEE Transaction on Fuzzy Systems, Accepted.

DOI: https://doi.org/10.1109/tfuzz.2004.839652

[4] Tafazoli, M., Demirli, K.: Fuzzy modeling of hysteresis from input-ouput data, IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th , 25-28 July 2001Pages: 3009 - 3014 vol. 5.

DOI: https://doi.org/10.1109/nafips.2001.943707

[5] Yufang Yue, Jianqin Mao:Approach of fuzzy modeling with bounded data uncertainties, the 15 th IFAC World Congress b'02 , Barcelona, Spain, 2002. 7.

DOI: https://doi.org/10.3182/20020721-6-es-1901.00384

[6] Fuzi, J.: Analytical approximation of Preisach distribution functions; Magnetics, IEEE Transactions on, Volume: 39, Issue: 3, May 2003 Pages: 1357 - 1360.

DOI: https://doi.org/10.1109/tmag.2003.810536

[7] Ragusa, C Analytical expressions of Preisach Distribution Function.; Magnetics Conference, 2002. INTERMAG Europe 2002. Digest of Technical Papers. 2002 IEEE International , 28 April-2 May 2002 Pages: FS3.

DOI: https://doi.org/10.1109/intmag.2002.1001346

[8] Wang, L. -X.: Fuzzy systems are universal approximators; Fuzzy Systems, 1992., IEEE International Conference on , 8-12 March 1992 Pages: 1163 - 1170.

DOI: https://doi.org/10.1109/fuzzy.1992.258721