title: Modeling of Rate-Dependent Hysteresis Using a GPO-Based Adaptive Filter.
abstract: 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.
authors: School of Automation Sciences and Electrical Engineering, Beihang University, XueYuan Road NO.37, Haidian District, Beijing 100191, China. zhangzhen@buaa.edu.cn.
authors: Zhen
authors: Z
authors: Zhang
authors: School of Automation Sciences and Electrical Engineering, Beihang University, XueYuan Road NO.37, Haidian District, Beijing 100191, China. mayaopengbuaa@163.com.
authors: Yaopeng
authors: Y
authors: Ma
keywords: LMS; adaptive filter; hysteresis; modeling; rate-dependent