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基于改进灰狼算法的电动缸摩擦辨识及补偿

王淑良 王彦涛 赵明伟 卞嘉志 刘丽俊

现代制造工程Issue(8):42-50,9.
现代制造工程Issue(8):42-50,9.DOI:10.16731/j.cnki.1671-3133.2024.08.006

基于改进灰狼算法的电动缸摩擦辨识及补偿

Electric cylinder friction identification and compensation control based on improved gray wolf optimization algorithm

王淑良 1王彦涛 1赵明伟 1卞嘉志 1刘丽俊1

作者信息

  • 1. 江苏师范大学电气工程及自动化学院,徐州 221116
  • 折叠

摘要

Abstract

Nonlinear friction for motorized cylinders is difficult to identify and adversely affects the tracking accuracy of the posi-tion of the six-degree-of-freedom Electrically Driven Stewart Platform(EDSP),an improved Gray Wolf Optimization algorithm in-troducing Levy flight and Cauchy variation(LCGWO)with Levy flight and Cauchy variation is proposed to identify the friction parameters of the electric cylinder,and a feed-forward compensation method based on the friction model is designed.Firstly,a mathematical model of EDSP considering the nonlinear friction of the electric cylinder is developed and the friction is described using the Lugre friction model.Then,considering that the nonlinear friction of the electric cylinder is difficult to identify,an LCG-WO is proposed to identify the static and dynamic parameters in the friction model at the same time,and compared and analyzed with the general identification method.Finally,a feed forward compensation algorithm based on the Lugre friction model is de-signed and experimentally verified.The experimental results show that compared with other algorithms,LCGWO has better conver-gence speed and prediction accuracy;and the friction compensation of the electric cylinder by the friction feed-forward compensa-tion method based on the friction model can effectively improve the platform's position tracking accuracy.

关键词

Stewart平台/电动缸/参数辨识/灰狼算法/摩擦补偿

Key words

Stewart platform/electric cylinder/parameter identification/GWO/friction compensation

分类

信息技术与安全科学

引用本文复制引用

王淑良,王彦涛,赵明伟,卞嘉志,刘丽俊..基于改进灰狼算法的电动缸摩擦辨识及补偿[J].现代制造工程,2024,(8):42-50,9.

基金项目

国家自然科学基金项目(61801197,61503166) (61801197,61503166)

现代制造工程

OA北大核心CSTPCD

1671-3133

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