压电陶瓷作动器的卡尔曼滤波输出反馈预测控制  

Kalman filter based output feedback predictive control for piezoelectric ceramic actuators

作　　者：于树友[1,2] 谭丽 李建普 冯阳阳 刘冬梅 林宝君 孙绍瑜[1] YU Shuyou;TAN Li;LI Jianpu;FENG Yangyang;LIU Dongmei;LIN Baojun;SUN Shaoyu(Department of Control Science and Engineering,Jilin University,Changchun 130012,China;Key Laboratory of Industrial Internet of Things and Networked Control,Ministry of Education,Chongqing University of Posts and Telecommunications,Chongqing 400065,China;College of Electronic and Information Engineering,Changchun University,Changchun 130022,China)

机构地区：[1]吉林大学控制科学与工程系,吉林长春130012 [2]重庆邮电大学工业物联网与网络化控制教育部重点实验室,重庆400065 [3]长春大学电子信息工程学院,吉林长春130022

出　　处：《光学精密工程》2024年第11期1724-1735,共12页Optics and Precision Engineering

基　　金：国家自然科学基金资助项目(No.U1964202);工业物联网与网络化控制教育部重点实验室基金资助项目(No.2019FF01);吉林省自然科学基金资助项目(No.YDZJ202101ZYTS169);吉林省教育厅科学技术研究项目(No.JJKH20220592KJ)。

摘　　要：为了抑制压电陶瓷的迟滞、非线性特性对压电微定位平台精度的影响,建立反映压电陶瓷作动器频率依赖迟滞非线性特性的Hammerstein模型:利用非对称Bouc-Wen模型来表示静态迟滞非线性和利用动态线性模型表征信号频率的影响。针对迟滞补偿器不能完全的进行补偿,并且存在噪音干扰实验设备,采用基于卡尔曼滤波的预测控制,提高压电微定位平台的控制精度。预测控制用来减小逆补偿误差以及建模误差等模型不确定性的影响,卡尔曼滤波用来获得系统的状态估计值。实验结果显示,该控制器在正弦波信号下的相对跟踪误差小于0.68%,三角波信号下相对跟踪误差小于0.70%。在迟滞补偿的基础上,采用卡尔曼滤波的预测控制,该方法可以有效地完成对微定位平台的高精度跟踪。To mitigate the influence of hysteresis and nonlinearity in piezoelectric ceramics on the accuracy of piezoelectric micropositioning platforms,the Hammerstein model is employed to describe the frequencydependent hysteretic nonlinearity of piezoelectric ceramic actuators.This model comprises an asymmetric Bouc-Wen model and a dynamic linear model to represent static hysteresis nonlinearity and frequency-dependent dynamic properties,respectively.Recognizing that the hysteresis compensator cannot entirely eliminate such issues and there is noise interference in experimental equipment,predictive control based on a Kalman filter is used to enhance the control accuracy of the piezoelectric micropositioning platform.Model predictive control addresses model uncertainties like inverse compensation errors and modeling errors,while the Kalman filter estimates the state of the system.Experimental results indicate that the relative tracking error of the proposed controller is less than 0.68%for sine wave signals and less than 0.70%for triangular wave signals.By incorporating Kalman filter-based predictive control alongside hysteresis compensation,the micropositioning platform effectively achieves high-precision tracking.

关 键 词：预测控制 卡尔曼滤波 压电陶瓷作动器 HAMMERSTEIN模型 

分 类 号：TP273.1[自动化与计算机技术—检测技术与自动化装置] TN384[自动化与计算机技术—控制科学与工程]