Identification of Asymmetric Bouc-Wen Model Based on Ga Algorithm for a Piezo-Actuated Stage

Abstract

In recent years, piezoelectric actuators (PEAs) are widely used in precision positioning stage due to its outstanding advantages of small size, high displacement resolution and fast response. However, in practical applications, PEAs are also affected by the inherent nonlinear factors such as hysteresis and creep, which further results the positioning accuracy deceasing of the stage. In this paper, a modified Bouc-Wen model is proposed to identify the hysteresis characteristics of PEAs. In order to improve the identification accuracy of the model, the modified Bouc-Wen model parameters are identified by the Genetic Algorithm (GA) which has a good global search capability. The experimental results show that the range of the absolute error (RAE) of the modified Bouc-Wen model is reduced by 5.87% and the average fitness value (AFV) is reduced by 4.87% compared to the standard Bouc-Wen model, which further validate the accuracy of the proposed modified Bouc-Wen model.