Abstract

Most smart materials used in engineering applications have rate-dependent hysteresis nonlinearity. In this paper, a Hammerstein-based model is proposed to describe the dynamic characteristics of rate-dependent hysteresis in piezoelectric actuator. A Bouc-Wen model is used to approximate the static nonlinear characteristic while a linear dynamic model is constructed to capture the rate-dependent property of the hysteresis. Firstly, Bouc-Wen model parameters are optimized with particle swarm optimization (PSO) algorithm to model the static hysteresis nonlinearity. Based on this constructed static hysteresis nonlinear model, a recursive least squares (RLS) algorithm is utilized to identify the dynamic linear model parameters of Hammerstein model according to the input-output data with rich frequency information. Finally, the experimental results of applying the proposed method to the modeling of rate-dependent hysteresis in a piezoelectric actuator are presented with a 100Hz sinusoidal scanning signal. The model generation capability is verified in the given frequency range from 1Hz to100Hz when the excitation voltage are 40V, 80V, 120V, respectively.

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