基于Rayleigh-BP模型的压电驱动系统迟滞建模与前馈控制  

Hysteresis Modeling and Feedforward Control for Piezoelectric Driven Systems Based on Rayleigh-BP Model

作　　者：张萌 范鹏举 王俊璞 刘时成 ZHANG Meng;FAN Pengju;WANG Junpu;LIU Shicheng(College of Mechanical and Electrical Engineering,Shaanxi University of Science&Technology,Xi'an,710021)

机构地区：[1]陕西科技大学机电工程学院,西安710021

出　　处：《中国机械工程》2024年第9期1597-1605,共9页China Mechanical Engineering

基　　金：陕西省自然科学基础研究计划(2023-JC-QN-0408)。

摘　　要：针对可调谐半导体激光器压电驱动系统的迟滞非线性,提出了一种基于Rayleigh-BP模型的建模及控制方法。利用空间扩展法建立了Rayleigh-BP率相关迟滞模型,该模型实现了对压电驱动系统的率相关迟滞非线性的精准预测;利用逆向算法求解了Rayleigh模型的逆模型,并将该模型与BP神经网络结合,设计了前馈控制器对系统进行补偿;对前馈控制方法进行了仿真与实验验证。结果表明,建立的Rayleigh-BP模型具有较高的精度,在10 Hz时均方根误差仅为0.0469μm。前馈控制方法可以明显提高系统输出的线性度,在40 Hz时仿真结果均方根误差为0.0274μm,线性相关系数R 2为0.99992;在30 Hz时实验结果均方根误差为0.0506μm,线性相关系数R 2达到了0.99955,极大降低了迟滞现象。Aiming at the hysteresis nonlinearity of the piezoelectric driven systems for tunable external cavity diode lasers,a modelling and control method was proposed herein based on Rayleigh-BP model.Firstly,a Rayleigh-BP rate-dependent hysteresis model was developed by spatial expansion method,which achieved an accurate prediction of rate-dependent hysteresis nonlinearity of piezoelectric driven systems.Secondly,the inverse model of Rayleigh model was solved by an inverse algorithm,and the model was combined with a BP neural network to design a feedforward controller to compensate the systems.Finally,the feedforward control method was validated by simulation and experiments.The results show that the Rayleigh-BP model developed has high accuracy,the root mean square error is only as 0.0469μm at 10 Hz.The feedforward control method may significantly improve the linearity of the system outputs,the root mean square error of the simulation results is as 0.0274μm and the linear correlation coefficient R 2 is as 0.99992 at 40 Hz.The experimental results show a root mean square error of 0.0506μm and a linear correlation coefficient R 2 of 0.99955 at 30 Hz,which greatly reduces the hysteresis phenomenon.

关 键 词：迟滞非线性 Rayleigh模型 反向传播(BP)神经网络 前馈控制 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]