Research on constant force grinding control of aero-engine blades based on extended state observer

IF 1.9 4区 计算机科学 Q3 ENGINEERING, INDUSTRIAL
Shijie Dai, Wenhua Zhang, Wenbin Ji, Yufeng Zhao, Hongwei Zheng, Jiaheng Mu, Pengwei Li, Riqing Deng
{"title":"Research on constant force grinding control of aero-engine blades based on extended state observer","authors":"Shijie Dai, Wenhua Zhang, Wenbin Ji, Yufeng Zhao, Hongwei Zheng, Jiaheng Mu, Pengwei Li, Riqing Deng","doi":"10.1108/ir-12-2021-0294","DOIUrl":null,"url":null,"abstract":"\nPurpose\nConsidering the influence of environmental noise and modeling error during the process of the robotic automatic grinding aero-engine blade, this study aims to propose a method based on the extended state observer (ESO) to reduce the fluctuation of normal grinding force.\n\n\nDesign/methodology/approach\nFirst, the measurement range of the six-dimensional force sensor is calibrated according to the maximum acceleration of end-effector and grinding force. Second, the gravity and zero drift compensation model is built to compensate for measurement error. Finally, the switching function is designed based on the difference between the expected grinding force and the actual feedback value. When the value of function stays within the switching band, a nonlinear active disturbance rejection control (ADRC) loop is applied. When the function value reaches outside the switching band, an ESO-based sliding mode control (SMC) loop is applied.\n\n\nFindings\nThe simulated and experimental results show that the proposed control method has higher robustness compared with proportion-integral-derivative (PID), Fuzzy PID and ADRC.\n\n\nResearch limitations/implications\nThe processing parameters of this paper are obtained based on the single-factor experiment without considering the correlation between these variables. A new control strategy is proposed, which is not only used to control the grinding force of blades but also promotes the development of industrial control.\n\n\nOriginality/value\nESO is used to observe environmental interference and modeling errors of the system for real-time compensation. The segment control method consisting of ESO-based SMC and ESO-based ADRC is designed to improve the robustness. The common application of the two parts realizes suppression of fluctuation of grinding force.\n","PeriodicalId":54987,"journal":{"name":"Industrial Robot-The International Journal of Robotics Research and Application","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2022-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Industrial Robot-The International Journal of Robotics Research and Application","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1108/ir-12-2021-0294","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 3

Abstract

Purpose Considering the influence of environmental noise and modeling error during the process of the robotic automatic grinding aero-engine blade, this study aims to propose a method based on the extended state observer (ESO) to reduce the fluctuation of normal grinding force. Design/methodology/approach First, the measurement range of the six-dimensional force sensor is calibrated according to the maximum acceleration of end-effector and grinding force. Second, the gravity and zero drift compensation model is built to compensate for measurement error. Finally, the switching function is designed based on the difference between the expected grinding force and the actual feedback value. When the value of function stays within the switching band, a nonlinear active disturbance rejection control (ADRC) loop is applied. When the function value reaches outside the switching band, an ESO-based sliding mode control (SMC) loop is applied. Findings The simulated and experimental results show that the proposed control method has higher robustness compared with proportion-integral-derivative (PID), Fuzzy PID and ADRC. Research limitations/implications The processing parameters of this paper are obtained based on the single-factor experiment without considering the correlation between these variables. A new control strategy is proposed, which is not only used to control the grinding force of blades but also promotes the development of industrial control. Originality/value ESO is used to observe environmental interference and modeling errors of the system for real-time compensation. The segment control method consisting of ESO-based SMC and ESO-based ADRC is designed to improve the robustness. The common application of the two parts realizes suppression of fluctuation of grinding force.
基于扩展状态观测器的航空发动机叶片恒力磨削控制研究
考虑到航空发动机叶片机器人自动磨削过程中环境噪声和建模误差的影响,提出了一种基于扩展状态观测器(ESO)的法向磨削力波动减小方法。首先,根据末端执行器的最大加速度和磨削力对六维力传感器的测量范围进行标定。其次,建立了重力和零漂移补偿模型,对测量误差进行补偿。最后,根据期望磨削力与实际反馈值的差值设计切换函数。当函数值保持在开关带内时,应用非线性自抗扰控制(ADRC)回路。当函数值达到开关带外时,应用基于eso的滑模控制(SMC)回路。仿真和实验结果表明,与比例积分导数(PID)、模糊PID和自抗扰控制器(ADRC)相比,所提控制方法具有更高的鲁棒性。研究局限性/意义本文的工艺参数是基于单因素实验得出的,没有考虑这些变量之间的相关性。提出了一种新的控制策略,不仅可用于控制叶片磨削力,而且可促进工业控制的发展。原创性/价值eso用于观察系统的环境干扰和建模误差,进行实时补偿。为了提高系统的鲁棒性,设计了基于eso的SMC和基于eso的自抗扰控制器的分段控制方法。两部分的共同应用实现了磨削力波动的抑制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
4.50
自引率
16.70%
发文量
86
审稿时长
5.7 months
期刊介绍: Industrial Robot publishes peer reviewed research articles, technology reviews and specially commissioned case studies. Each issue includes high quality content covering all aspects of robotic technology, and reflecting the most interesting and strategically important research and development activities from around the world. The journal’s policy of not publishing work that has only been tested in simulation means that only the very best and most practical research articles are included. This ensures that the material that is published has real relevance and value for commercial manufacturing and research organizations. Industrial Robot''s coverage includes, but is not restricted to: Automatic assembly Flexible manufacturing Programming optimisation Simulation and offline programming Service robots Autonomous robots Swarm intelligence Humanoid robots Prosthetics and exoskeletons Machine intelligence Military robots Underwater and aerial robots Cooperative robots Flexible grippers and tactile sensing Robot vision Teleoperation Mobile robots Search and rescue robots Robot welding Collision avoidance Robotic machining Surgical robots Call for Papers 2020 AI for Autonomous Unmanned Systems Agricultural Robot Brain-Computer Interfaces for Human-Robot Interaction Cooperative Robots Robots for Environmental Monitoring Rehabilitation Robots Wearable Robotics/Exoskeletons.
文献相关原料
公司名称 产品信息 采购帮参考价格
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信