组合机床与自动化加工技术2024,Issue(9) :104-107.DOI:10.13462/j.cnki.mmtamt.2024.09.021

基于最小辨识误差的机器人拖动控制系统设计

Design of Robot Drag Control System Based on Minimum Identification Error

陈燊豪 毛世鑫 吴蕾
组合机床与自动化加工技术2024,Issue(9) :104-107.DOI:10.13462/j.cnki.mmtamt.2024.09.021

基于最小辨识误差的机器人拖动控制系统设计

Design of Robot Drag Control System Based on Minimum Identification Error

陈燊豪 1毛世鑫 2吴蕾3
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作者信息

  • 1. 广东工业大学机电工程学院,广州 510006
  • 2. 九天创新(广东)智能科技有限公司,佛山 528299
  • 3. 工业和信息化部电子第五研究所,广州 511370
  • 折叠

摘要

传统的拖动示教算法主要通过动力学模型补偿的方式补偿系统的惯性项和重力项,但由于动力学模型的不准确性导致拖动性能变差.基于关节力传感器,提出仅需通过重力辨识得到的模型实现拖动示教控制的效果.对于重力模型辨识,在LSM的基础上设计误差代价函数,根据代价函数得到误差迭代表达式,使模型估计参数进一步迭代收敛于真实值,实现对协作机器人重力模型的精确辨识.同时,基于重力模型设计拖动控制器,实现柔顺拖动控制.最后,通过MATLAB-Simlink联合仿真,并在搭建的协作机器人平台上验证,结果表明提出的辨识方法具有更高的收敛精度,基于重力模型的拖动控制系统具有更高的稳定性和柔顺性.

Abstract

The traditional drag-teaching algorithm mainly compensates the inertia and gravity terms of the system by means of dynamic model compensation,but the performance of drag-teaching is poor due to the inaccuracy of the dynamic model.Based on the joint force sensor,this paper proposes that only the model obtained by gravity identification can achieve the effect of drag teaching control.For the gravity model i-dentification,the error cost function is designed based on LSM,and the error iterative expression is obtained according to the cost function,so that the model estimation parameters are further iteratively convergent to the true value,and the accurate identification of the collaborative robot gravity model is realized.At the same time,the drag controller is designed based on the gravity model to realize the smooth drag control.Fi-nally,through MATLAB-Simlink co-simulation and verification on the collaborative robot platform built in our laboratory,the results show that the proposed identification method has higher convergence accuracy,and the drag control system based on gravity model has higher stability and flexibility.

关键词

机器人/重力辨识/代价函数/误差迭代/拖动控制器

Key words

robots/gravity identification/cost function/error iteration/drag control

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基金项目

国家自然科学基金项目(51605096)

广东省科技创新战略专项资金项目(pdjh2022a0148)

出版年

2024
组合机床与自动化加工技术
大连组合机床研究所 中国机械工程学会生产工程分会

组合机床与自动化加工技术

CSTPCD北大核心
影响因子:0.671
ISSN:1001-2265
参考文献量1
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