Parameter Identification and Hysteresis Compensation for Piezoelectric Stack Based on Bouc-Wen Model Using Genetic Algorithm

Piezoelectric stack (PS) has been widely used as a high precision actuator in micro-vibration control of precision structures due to its small volume, fast frequency response, high resolution and so on. However, its hysteretic nonlinear behavior limits the modeling and control accuracy. Therefore, describing the hysteresis characteristic of PS by appropriate mathematical model is a prime choice for hysteresis compensation. In this paper, Bouc-Wen model is used to capture the hysteresis of PS. Considering the strong adaptability and global optimization performance of Genetic Algorithm (GA), the model parameters are evaluated by optimization based on GA. During the identification process, the parameter interval is continuously narrowed according to the fitness function and the identification result, so as to effectively improve the convergence speed of the algorithm. At the same time, an inverse Bouc-Wen model compensator is adopted to eliminate the hysteresis. Finally, the identification and compensation of the hysteresis for PS are verified by experiments. The experimental results demonstrate that the hysteresis of PS can be correspondingly compensated without additional computation.