The inherent rate-dependent hysteresis non-linearity of a piezoelectric micro-positioning station seriously limits its micro-positioning accuracy. To solve this problem, the Hammerstein rate-dependent hysteresis nonlinear model based on Backlash-Like hysteresis and its modeling method were investigated in this study. An improved Backlash-Like piece-wise identification model was first utilized to describe the static nonlinear characteristics of the piezoelectric micro-positioning station. Combined with the Auto Regressive eXogenous(ARX) model, a rate-dependent dynamic hysteresis model was then established to describe the piezoelectric micro-positioning station. In addition, to solve the problem in which the traditional Particle Swarm Optimization (PSO) method easily falls into a local optimum, an improved PSO method using a cross-mutation strategy was proposed to identify the parameters of the model. The experimental results show that, compared to the traditional Backlash-Like model, the maximum error of model identification is reduced from 0.68 μm to 0.104 μm and the maximum relative error is reduced from 2.69% to 0.35% when the input voltage is 60 V and the voltage frequency is a single-frequency signal of 2 Hz. In addition, when the input voltage of the piezoelectric micro-positioning station is 60 V and the voltage frequency is a single-frequency signal of 30, 60, and 90 Hz, as compared with the Backlash-Like piece-wise identification model, the root mean square error of the Hammerstein rate-dependent hysteresis model decrease from 0.338 7-0.700 6 to 0.035 1-0.190 4, and the relative error decrease from 1.478%-3.087% to 0.153%-0.831%. It was verified that the rate-dependent hysteresis model based on the improved Backlash-Like model could more accurately describe the rate-dependent dynamic hysteresis characteristics of a piezoelectric micro-positioning station as compared with the traditional Backlash-Like static hysteresis model. In addition, the model showed better frequency generalization, and the positioning accuracy of the piezoelectric micro-positioning platform was improved.