Rate-Dependent Hysteresis Modeling of Piezoceramic Actuators and Parameter Identification with an Improved Genetic Algorithm

To improve the positioning accuracy of piezoceramic actuators, this study proposes a rate-dependent hysteresis nonlinear model based on the Hammerstein model and its modeling method. The model uses the classic Bouc-Wen model to describe the static characteristics of the actuator and the ARMAX model to describe its dynamic characteristics. To solve the problem that the traditional particle swarm optimization algorithm is prone to falling into local optima in model parameter identification, this paper introduces an improved genetic algorithm for parameter identification. Experimental results show that the Hammerstein model based on Bouc-Wen and ARMAX can accurately describe the rate-dependent hysteresis characteristics of piezoceramic actuators, effectively improving the accuracy of the actuator.