基于自学习非线性PID的音圈电机精密定位系统  

A Voice Coil Motor-Driven Precision Positioning System Based on Self-Learning Nonlinear PID

作　　者：程苗苗[1] 翟朋辉 张英杰 李健[2] 冯凯 Cheng Miaomiao;Zhai Penghui;Zhang Yingjie;Li Jian;Feng Kai(School of Electrical and Information Engineering Hunan University,Changsha 410082,China;School of Mechanical and Vehicle Engineering Hunan University,Changsha 410082,China)

机构地区：[1]湖南大学电气与信息工程学院,长沙410082 [2]湖南大学机械与运载工程学院,长沙410082

出　　处：《电工技术学报》2023年第6期1519-1530,共12页Transactions of China Electrotechnical Society

基　　金：国家重点研发计划资助项目(2020YFB2007604)。

摘　　要：基于音圈电机的精密宏微气浮运动系统,是一种能克服接触摩擦和行程限制的新型精密定位系统。针对系统中用于精密定位的音圈电机受到内外扰动从而影响系统最终定位精度的问题,在建立起音圈电机数学模型的基础上,设计了基于反正弦函数的自学习非线性PID控制器,利用自学习算法对非线性增益函数的增益系数进行实时调整。完成算法设计与仿真后,在搭建的系统平台分别进行了微动台短行程定位和宏微动台的长行程定位实验。仿真和实验结果表明,与传统PID控制器相比较,自学习非线性PID控制器的使用有效提高了系统的鲁棒性和定位精度,系统对位置指令响应迅速无超调,控制精度达到了亚微米级。As a typical precise-positioning and long-stroke motion system,the precision macro-micro air-floating motion table has been taking more and more research interest due to its free-of-contact friction characteristics.Voice coil motor(VCM)has been proposed as the main driving element for the micro motion table due to its fast response and non-contact feed drives.However,due to the mover suspending to the stator,VCM is susceptible to interference such as load disturbance,vibration,and noise.Some solutions have been proposed in the existing research to eliminate the disturbances and improve positioning accuracy.However,either limited effect or complex implementation problems exist.Therefore,this paper proposes a novel self-learning nonlinear PID control method to improve the positioning accuracy and robustness of the VCM precision positioning system.The main idea of the proposed control method is to construct a nonlinear PID control law based on the arcsine function,and apply the neural network algorithm to adaptively adjust the weight parameters of the proposed nonlinear function with the time-varying system errors.Accordingly,the pre-designed PID control law assures the PID control parameters change reasonably by following the proposed arcsine function.The BP neural network can provide control flexibility,thus improving the model robustness and control accuracy.Therefore,the proposed self-learning nonlinear PID control is the potential for nonlinear,multivariable,and interference-susceptible systems,such as the precision macro-micro air-floating motion system.The unit step response experiment is first performed on the micromotion table.The experimental results show that the overshoot of the traditional PID controller is about 8%,and the steady-state positioning accuracy is 1μm.The steady-state positioning accuracy of the self-learning nonlinear PID controller is 0.5μm,and there is no overshoot.The proposed method provides better positioning accuracy and transient response.Some experiments are further carried out w

关 键 词：精密宏微气浮运动系统 音圈电机 自学习非线性PID 定位精度 

分 类 号：TM359.4[电气工程—电机]