A comparison of fitness functions for the identification of a piezoelectric hysteretic actuator based on the real-coded genetic algorithm

Abstract

The main objective of this study is to identify the piezoelectric actuator (PA) with hysteresis, which is described by Bouc-Wen model. The identification method based on real-coded genetic algorithm (RGA) has the advantages not only to identify the parameters of the hysteresis model but also the mass, stiffness, damping coefficient and piezoelectric coefficient of the PA simultaneously. Furthermore, the selection of fitness functions in the RGA is the key point to influence the final identified results. In this paper, three types of fitness functions are designed to identify the hysteretic PA and their differences are discussed. The numerical simulations and experimental results demonstrate that the identification method based on the RGA with suitable fitness functions is feasible.