Study on dynamic hysteresis characteristic modeling and parameter identification methods for high-voltage piezoelectric actuators

高压压电作动器动态迟滞特性建模及参数辨识方法研究

¹ School of Sciences, Chang′an University, Xi′an 710064, China
² School of Aerospace Engineering, Xi′an Jiaotong University, Xi′an 710049, China
³ School of Aeronautics, Northwestern Polytechnical University, Xi′an 710072, China

Received: 8 July 2024

Abstract

High-voltage piezoelectric actuators are widely used in the field of active vibration control of aerospace structures due to their advantages of strong load capacity, large nominal thrust, and fast response. However, its inherent hysteresis characteristics will affect the efficiency and stability of the piezoelectric active control system. Aiming at the problem of hysteresis characteristic modeling and parameter identification in high-voltage piezoelectric actuators, a dynamic hysteresis characteristic modeling and parameter identification method for piezoelectric actuators based on the Hammerstein model and a modified adaptive particle swarm optimization algorithm is proposed. Firstly, the asymmetric Bouc-Wen model is used to describe the static hysteresis effect. Combining with the transfer function model further, the Hammerstein rate-dependent dynamic hysteresis model for high-voltage piezoelectric actuator is constructed. Secondly, a modified adaptive particle swarm optimization algorithm is proposed based on the nonlinear decreasing inertia weight strategy and dynamic learning factors, and the hysteresis model parameters are identified by using the hysteresis characteristic experimental data of the high-voltage piezoelectric actuator, which verifies the superiority of the present algorithm over the traditional particle swarm optimization algorithm. Thirdly, the hysteresis effect prediction experiments of the high-voltage piezoelectric actuator demonstrate that the established Hammerstein model can efficiently describe its dynamic hysteresis effect and has a strong adaptability to the changes in the frequency and amplitude of the actuator driving voltage in the concerned frequency band.

摘要

高压压电作动器因其具有负载能力强、标称推力大、响应速度快等优点而被广泛应用于航空、航天结构振动主动控制领域。然而，其固有的迟滞特性会直接影响压电主动控制系统的效能和稳定性。针对高压压电作动器迟滞特性建模及参数辨识问题，提出了一种基于Hammerstein模型和改进型自适应粒子群算法的压电作动器动态迟滞特性建模及参数辨识方法。采用非对称Bouc-Wen模型描述静态迟滞效应，进一步结合传递函数模型，构造了高压压电作动器的Hammerstein率相关动态迟滞模型。基于非线性递减惯性权重策略和动态学习因子，提出了一种改进型自适应粒子群算法，并使用高压压电作动器迟滞特性测试实验数据辨识得到了迟滞模型参数，验证了所提算法相较于传统粒子群算法的优越性。通过高压压电作动器迟滞效应预测实验，验证了所建立的Hammerstein模型可以高效预测动态迟滞效应，且在关心频带内对于作动器驱动电压频率和幅值的改变具有很强的适应性。