一种基于BP神经网络的压电陶瓷驱动器控制方法研究  

Research on a control method of piezoelectric ceramic actuator based on BP neural network

作　　者：王桂莲[1,2] 陈江洋 邓誉鑫 张善青[1,2] WANG Guilian;CHEN Jiangyang;DENG Yuxin;ZHANG Shanqing(Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control,Tianjin University of Technology,Tianjin 300384,China;National Demonstration Center for Experimental Mechanical and Electrical Engineering Education,Tianjin University of Technology,Tianjin 300384,China)

机构地区：[1]天津理工大学天津市先进机电系统设计与智能控制重点实验室,天津300384 [2]天津理工大学机电工程国家级实验教学示范中心,天津300384

出　　处：《天津理工大学学报》2024年第6期78-86,共9页Journal of Tianjin University of Technology

基　　金：天津市多元投入基金项目重点项目(21JCZDJC00870);天津市研究生科研创新项目(2021YJSS094)。

摘　　要：压电陶瓷驱动器在微定位技术中得到了广泛应用,但压电陶瓷的迟滞非线性严重影响了微定位平台的定位精度。因此,为了提高微定位平台的定位精度和响应速度,提出了一种基于反向传播(back propagation,BP)神经网络的压电陶瓷驱动器迟滞非线性补偿方法,以用于进一步对微定位平台控制系统进行研究。首先,通过Prandtl-Ishlinskii(PI)模型确定了神经网络的输入和输出;其次,采集了用于训练神经网络的数据集并对神经网络进行了训练,同时得出了最佳的隐藏层神经元个数;最后,使用训练好的神经网络对压电陶瓷驱动器进行了控制效果测试。实验结果表明,使用该方法来控制压电陶瓷驱动器,可以使其输出位移与理论位移基本相同,验证了神经网络补偿压电陶瓷迟滞非线性的有效性。Piezoelectric ceramic actuators are widely used in micro-positioning technology,but the hysteresis nonlinearity of piezoelectric ceramics seriously affects the positioning accuracy of micro-positioning platforms.Therefore,in order to improve the positioning accuracy and response speed of the micro-positioning platform,a back propagation(BP) neural network-based hysteresis nonlinearity compensation method for piezoelectric ceramic actuators is proposed for further study of the micro-positioning platform control system.First,the input and output of the neural network are determined by the Prandtl-Ishlinskii(PI) model.Second,the data set for training the neural network is collected and the nural network is trained,and the optimal number of hidden layer neurons is derived.Finally,the control effect of the piezoelectric ceramic actuator is tested using the trained neural network.The experimental results show that using this method to control the piezoelectric ceramic actuator can make its output displacement almost the same as the theoretical displacement,which verifies the effectiveness of the neural network to compensate the piezoelectric ceramic hysteresis nonlinearity.

关 键 词：压电陶瓷 反向传播神经网络 迟滞非线性 前馈控制 

分 类 号：TP273.5[自动化与计算机技术—检测技术与自动化装置]