Chin. Phys. B, 2018, Vol. 27(9): 098503    DOI: 10.1088/1674-1056/27/9/098503
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# Modeling and identification of magnetostrictive hysteresis with a modified rate-independent Prandtl-Ishlinskii model

Wei Wang(王伟)1,3, Jun-en Yao(姚骏恩)1,2,3
1 School of Instrumentation Science and Opto-electronics Engineering, Beihang University, Beijing 100083, China;
2 School of Physics and Nuclear Energy Engineering, Beihang University, Beijing 100083, China;
3 Laboratory of Micro-nano Measurement, Manipulation and Physics, Beihang University, Beijing 100083, China
Abstract

This paper presents a modified rate-independent Prandtl-Ishlinskii (MRIPI) model based on the Fermi-Dirac distribution for the asymmetric hysteresis description of magnetostrictive actuators. Generally, the classical Prandtl-Ishlinskii (CPI) model can hardly describe the asymmetric hysteresis. To overcome this limitation, various complex operators have been developed to replace the classical operator. In this study, the proposed MRIPI model maintains the classical operator while a modified input function based on the Fermi-Dirac distribution is presented to replace the classical input function. With this method, the MRIPI model can describe the asymmetric hysteresis of magnetostrictive actuators in a relatively simple mathematic format and has fewer parameters to be identified. A velocity-based sine cosine algorithm (VSCA) is also proposed for the parameter identification of the MRIPI model. To verify the validity of the MRIPI model, experiments are performed and the results are compared with those of the existing modeling methods.

Keywords:  Prandtl-Ishlinskii model      velocity-based sine cosine algorithm      asymmetric hysteresis nonlinearity      magnetostrictive actuator
Received:  12 March 2018      Revised:  20 June 2018      Accepted manuscript online:
 PACS: 85.70.Ec (Magnetostrictive, magnetoacoustic, and magnetostatic devices) 75.60.-d (Domain effects, magnetization curves, and hysteresis)
Corresponding Authors:  Jun-en Yao     E-mail:  yaojen@cae.cn