• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2019, Vol. 55 ›› Issue (9): 136-143.doi: 10.3901/JME.2019.09.136

• 数字化设计与制造 • 上一篇    下一篇

基于GMM的高性能微定位工作台驱动系统的研制

喻曹丰, 王传礼, 解甜, 杨林建, 姜志   

  1. 安徽理工大学机械工程学院 淮南 232001
  • 收稿日期:2018-05-11 修回日期:2018-12-18 出版日期:2019-05-05 发布日期:2019-05-05
  • 通讯作者: 王传礼(通信作者),男,1964年出生,博士,教授,博士研究生导师。主要研究方向为流体传动与控制技术、功能材料应用及新型液压元件开发。E-mail:chlwang@aust.edu.cn
  • 作者简介:喻曹丰,男,1987年出生,博士,讲师。主要研究方向为精密驱动与控制技术。E-mail:yucaofeng@aust.edu.cn
  • 基金资助:
    国家自然科学基金(51075001,51675003,51705003)、安徽省2018年度重点研究与开发计划(1804a09020016)和安徽理工大学青年教师科学研究基金(QN 2018102)资助项目。

Development of Drive System of High Performance Micro Positioning Worktable Based on Giant Magnetostrictive Material

YU Caofeng, WANG Chuanli, XIE Tian, YANG Linjian, JIANG Zhi   

  1. School of Mechanical Engineering, Anhui University of Science and Technology, Huainan 232001
  • Received:2018-05-11 Revised:2018-12-18 Online:2019-05-05 Published:2019-05-05

摘要: 提高微定位工作台的性能是提升高端制造装备加工性能的重要方式之一,针对现有微定位工作台驱动系统存有驱动力小、行程短、定位精度低等问题,研制了一台以超磁致伸缩材料为核心元件微定位工作台的驱动系统。为提高驱动系统输出位移的建模精度,以Jiles-Atherton磁滞模型为基础,建立该驱动系统的输出位移模型;为提高模型参数的辨识精度,将粒子群算法快速局部搜索性与人工鱼群算法全局收敛性相结合,提出一种高精度的混合优化参数辨识算法;为补偿驱动系统的输出位移误差,引入一种动态递归神经网络前馈-模糊PID反馈控制策略;为提高程序的执行效率,采用了高速DSP芯片开发控制系统;通过研制样机,搭建试验平台进行验证。结果表明:所研制驱动系统的最大位移为30.8 μm,最大输出力为292.3 N,定位精度达到0.75 μm,最大重复性误差为0.4 μm,为研制高性能精密定位装置奠定了理论基础。

关键词: 超磁致伸缩材料, 磁滞非线性, 混合优化算法, 控制策略

Abstract: Improving the performance of a micro positioning worktable is one of major approaches used to improve the processing performance of high-end manufacturing equipment. Aiming at the problems such as low drive force, short stroke and low positioning accuracy existing in the drive system of existing micro positioning worktable, a drive system of micro positioning worktable taking the giant magnetostrictive material as the core component is developed. In order to improve modeling accuracy of output displacement of the drive system, an output displacement model of the drive system is set up based on the Jiles-Atherton hysteresis model. In addition, in order to improve the identification precision of model parameters, a hybrid optimization parameter identification algorithm which has high accuracy and combines the rapid local search function of particle swarm algorithm and the global convergence of artificial fish swarm algorithm is proposed. And in order to compensate the output displacement error of the drive system, a dynamic recurrent neural network feedforward-fuzzy PID feedback control strategy is introduced. And in order to improve the execution efficiency of the program, a high-speed DSP chip is used to develop the control system. The prototype is built and verified with the experimental platform established. The research results indicate that the maximum displacement of the developed drive system is 30.8 μm, the maximum output force is 292.3 N, the positioning accuracy is 0.75 μm and the maximum repeatability error is 0.4 μm. This result lays a theoretical foundation for development of high-performance precision positioning devices.

Key words: control strategy, giant magnetostrictive material, hysteresis nonlinear characteristic, mixed optimization algorithm

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