Modeling of Rate-Dependent Hysteresis Using a GPO-Based Adaptive Filter
AbstractA 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
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Zhang, Z.; Ma, Y. Modeling of Rate-Dependent Hysteresis Using a GPO-Based Adaptive Filter. Sensors 2016, 16, 205.
Zhang Z, Ma Y. Modeling of Rate-Dependent Hysteresis Using a GPO-Based Adaptive Filter. Sensors. 2016; 16(2):205.Chicago/Turabian Style
Zhang, Zhen; Ma, Yaopeng. 2016. "Modeling of Rate-Dependent Hysteresis Using a GPO-Based Adaptive Filter." Sensors 16, no. 2: 205.
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