Modeling of Rate-Dependent Hysteresis Using a GPO-Based Adaptive Filter

Sensors

Zhen Zhang¹  Yaopeng Ma¹ 

[1]School of Automation Sciences and Electrical Engineering, Beihang University, XueYuan Road NO.37, Haidian District, Beijing 100191, China

关键词: hysteresis;    rate-dependent;    adaptive filter;    LMS;    modeling;   

DOI  :  10.3390/s16020205

来源: DOAJ

【 摘 要 】

A novel generalized play operator-based (GPO-based) nonlinear adaptive filter is proposed to model rate-dependent hysteresis nonlinearity for smart actuators. In the proposed filter, the input signal vector consists of the output of a tapped delay line. GPOs with various thresholds are used to construct a nonlinear network and connected with the input signals. The output signal of the filter is composed of a linear combination of signals from the output of GPOs. The least-mean-square (LMS) algorithm is used to adjust the weights of the nonlinear filter. The modeling results of four adaptive filter methods are compared: GPO-based adaptive filter, Volterra filter, backlash filter and linear adaptive filter. Moreover, a phenomenological operator-based model, the rate-dependent generalized Prandtl-Ishlinskii (RDGPI) model, is compared to the proposed adaptive filter. The various rate-dependent modeling methods are applied to model the rate-dependent hysteresis of a giant magnetostrictive actuator (GMA). It is shown from the modeling results that the GPO-based adaptive filter can describe the rate-dependent hysteresis nonlinear of the GMA more accurately and effectively.

【 授权许可】

Unknown