Real-time adaptive inverse control based on neural networks for piezoceramic actuator with nonlinear and no-smooth hysteresis characteristic

Dang Xuan-ju

doi:null

您当前的位置：

首页 >

文章列表页 >

Real-time adaptive inverse control based on neural networks for piezoceramic actuator with nonlinear and no-smooth hysteresis characteristic

Article | 更新时间：2020-08-12

- Real-time adaptive inverse control based on neural networks for piezoceramic actuator with nonlinear and no-smooth hysteresis characteristic
- Optics and Precision Engineering Vol. 16, Issue 7, Pages: 1266-1272(2008)
- 作者机构：
  
  桂林电子科技大学计算机与控制学院
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Received：02 December 2007，
  
  Revised：19 January 2008，
  
  Published Online：25 July 2008，
  
  Published：25 July 2008
- 稿件说明：
移动端阅览
党选举. 压电陶瓷执行器的神经网络实时自适应逆控制[J]. 光学精密工程, 2008,16(7):1266-1272

Dang Xuan-ju. Real-time adaptive inverse control based on neural networks for piezoceramic actuator with nonlinear and no-smooth hysteresis characteristic[J]. Optics and precision engineering, 2008, 16(7): 1266-1272.
党选举. 压电陶瓷执行器的神经网络实时自适应逆控制[J]. 光学精密工程, 2008,16(7):1266-1272 DOI：

Dang Xuan-ju. Real-time adaptive inverse control based on neural networks for piezoceramic actuator with nonlinear and no-smooth hysteresis characteristic[J]. Optics and precision engineering, 2008, 16(7): 1266-1272. DOI：

摘要

目的：为了提高压电陶瓷执行器执行精度，提出消除压电陶瓷的非线性、非光滑的迟滞特性的方法。方法：提出了基于内积的压电陶瓷动态神经网络非线性、非光滑的迟滞逆模型，采用反馈误差学习方法，避免了求取压电陶瓷的Jacobian信息，快速地在线得到压电陶瓷的逆模型，并结合PID反馈控制，在dSPACE系统平台上，实现压电陶瓷的神经网络自适应逆控制

为了提高实时性，程序采用效率高、速度快的C-MEX S Function编程。结果：实验结果表明：神经网络自适应逆控制的控制精度为：0.13μm

而PID控制精度为：0.32μm 。结论：所提出方法有效地消除了迟滞的影响，控制精度高。

Abstract

Objetive: In order to improve the actuator precision，a method for eliminating nonlinear no-smooth hysteresis characteristic of piezoceramic actuator is proposed. Method :An inner product-based dynamic neural network nonlinear and no-smooth hysteresis inverse model for piezoceramic is obtained

in which the feedback error learning method is used to avoid obtaining Jacobian information by model for piezoceramic. On dSPACE system platform，the piezoceramic is controlled by combined with a PID control and an neural networks adaptive inverse control. In order to satisfy the requirement of real time control

the programs is designed by a high efficiency and fast C-MEX S function. Result: Experimental results indicate that the precision of the proposed adaptive inverse control based on neural networks is 0.13μm

PID control precision is 0.32μm. Conclusion: The proposed control method removes efficiently the hysteresis characteristic of piezoceramic and of higher control precision.

关键词

Keywords

references

Views

489

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Feed-forward control of piezoelectric ceramic positioning stage

Inverse control algorithm to compensate the hysteresis and creep effect of piezoceramic

Related Author

WANG Li

RAO Chang-hui

RAO Xue-jun

WANG Yue-yu

ZHAO Xue-zeng

Related Institution

Institute of Optics and Electronics, Chinese Academy of Sciences

Key Laboratory on Adaptive Optics, Chinese Academy of Sciences

Graduate University of Chinese Academy of Sciences

School of Mechatronics Engineering, Harbin Institute of Technology

AI问答

Address：No.3888 Dong Nanhu Road, Changchun, Jilin, China Postal code：130033
Tel：0431-86176855 Email：gxjmgc@ciomp.ac.cn
Technical support is provided by Beijing Founder electronics co., LTD 吉ICP备11002662号-17 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰