Comprehensive parameter identification of feed servo systems with friction based on responses of the worktable

被引：18
|
作者：
Liu, Lilan [1 ]
Wu, Ziying [1 ]
机构：
[1] Xian Univ Technol, Sch Mech Engn, Xian 710048, Shaanxi Provinc, Peoples R China
来源：
MECHANICAL SYSTEMS AND SIGNAL PROCESSING | 2015年 / 64-65卷
基金：
中国国家自然科学基金;
关键词：
Feed system; Parameter identification; Nonlinear least square method; Direct graphical registration method; SCREW DRIVEN SERVOMECHANISMS;
D O I：
10.1016/j.ymssp.2015.04.012
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
A comprehensive identification method for structure and friction parameters of feed servo systems is put forward. A motor direct-connected feed system with Stribeck friction law is investigated. The relation between the critical stick-slip velocity of the worktable and the structure parameters as well as the difference between the static and Coulomb friction coefficient is derived first. Then, according to the data of critical stick-slip velocities at different feed positions, the structural parameters (such as diameter, lead and bearing length of the ball screw) are estimated using the nonlinear least square method. Furthermore, based on the stick-slip displacement response of the worktable, the Stribeck friction parameters are obtained using the direct graphical registration method. The feasibility and validity of the presented identification method is verified by numerical simulation. All the work can provide a theoretical reference for the comprehensive parameters identification of feed systems. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码：257 / 265
页数：9
相关论文
共 50 条
  • [1] Research on parameter identification of friction model for servo systems based on genetic algorithms
    Liu, DP
    [J]. PROCEEDINGS OF 2005 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-9, 2005, : 1116 - 1120
  • [2] An Improved Parameter Identification Algorithm for the Friction Model of Electro-Hydraulic Servo Systems
    Liao, Jian
    Zhou, Fuming
    Zheng, Jianbo
    [J]. SENSORS, 2023, 23 (04)
  • [3] Effective parameter identification of the GMS friction model for feed systems in CNC machines
    Huang, Dehai
    Yang, Jianzhong
    Xu, Guangda
    Zhou, Huicheng
    Chen, Jiakang
    [J]. CONTROL ENGINEERING PRACTICE, 2024, 152
  • [4] Genetic algorithms based parameter identification for nonlinear mechanical servo systems
    Liu Depeng
    [J]. 2006 1ST IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, VOLS 1-3, 2006, : 1184 - 1188
  • [5] Genetic algorithms based parameter identification for nonlinear mechanical servo systems
    Liu Depeng
    [J]. ICIEA 2006: 1ST IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, VOLS 1-3, PROCEEDINGS, 2006, : 1014 - 1018
  • [6] Parameter identification of LuGre friction model for servo system based on improved particle swarm optimization algorithm
    Zhang Wenjing
    [J]. PROCEEDINGS OF THE 26TH CHINESE CONTROL CONFERENCE, VOL 3, 2007, : 135 - 139
  • [7] Frequency-domain identification algorithms for servo systems with friction
    Chen, YY
    Huang, PY
    Yen, JY
    [J]. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2002, 10 (05) : 654 - 665
  • [8] Direct identification for the continuous models of servo systems with friction nonlinearity
    Gan, Ming-Gang
    Gong, Wei-Guang
    Zhang, Guo-Zhu
    Chen, Jie
    Cai, Tao
    [J]. Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology, 2010, 30 (SUPPL. 1): : 86 - 90
  • [9] Position Control of Servo Systems Using Feed-Forward Friction Compensation
    Park, Min Gyu
    Kim, Han Me
    Shin, Jong Min
    Kim, Jong Shik
    [J]. TRANSACTIONS OF THE KOREAN SOCIETY OF MECHANICAL ENGINEERS A, 2009, 33 (05) : 508 - 513
  • [10] Model-based parameter identification of comprehensive friction behaviors for giant forging press
    李毅波
    潘晴
    黄明辉
    [J]. Journal of Central South University, 2013, 20 (09) : 2359 - 2365
12345