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Sensors 2016, 16(2), 205;

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

School of Automation Sciences and Electrical Engineering, Beihang University, XueYuan Road NO.37, Haidian District, Beijing 100191, China
Authors to whom correspondence should be addressed.
Academic Editor: Vittorio M.N. Passaro
Received: 26 November 2015 / Accepted: 27 January 2016 / Published: 6 February 2016
(This article belongs to the Section Physical Sensors)
Full-Text   |   PDF [3168 KB, uploaded 6 February 2016]   |  


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. View Full-Text
Keywords: hysteresis; rate-dependent; adaptive filter; LMS; modeling hysteresis; rate-dependent; adaptive filter; LMS; modeling

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Zhang, Z.; Ma, Y. Modeling of Rate-Dependent Hysteresis Using a GPO-Based Adaptive Filter. Sensors 2016, 16, 205.

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