Disturbance compensation based robust backstepping control for 2-DOF electro-hydraulic tunneling robot

IF 1.5 4区 工程技术 Q3 ENGINEERING, MECHANICAL
Guotai Zhang, Gang Shen, Tenbo Ye, Dong Liu, Yu Tang, Xiang Li, Yongcun Guo
{"title":"Disturbance compensation based robust backstepping control for 2-DOF electro-hydraulic tunneling robot","authors":"Guotai Zhang, Gang Shen, Tenbo Ye, Dong Liu, Yu Tang, Xiang Li, Yongcun Guo","doi":"10.1007/s12206-024-0837-y","DOIUrl":null,"url":null,"abstract":"<p>In order to suppress the influence of uncertain disturbances on the trajectory tracking of hydraulic manipulator, a composite control strategy for the cutting electro-hydraulic driving system (CEHDS) of the tunneling robot is presented, which synthesizes the advantages of neural networks technique, recursive backstepping and adaptive control theory. The Lagrangian model with actuator dynamics is derived based on the practical tunneling robot. The back-stepping method is utilized for the strictly feedback state-space model. To address the matched and unmatched lumped uncertainties, the radial-basis-function neural networks (RBFNNs) are employed to approximate the unmatched term which contains the nonlinear friction torque and external cutting load in the mechanical subsystem. The nonlinear disturbance observer (NDOB) is utilized to estimate the matched lumped uncertainty in the hydraulic subsystem. Simultaneously, the adaptive robust mechanism is proposed to compensate the residual disturbances. Based on the Lyapunov theorem, the stability and the bounded tracking error of the CEHDS are obtained. The simulation and experimental results validate the effectiveness of the proposed method in comparison with the common backstepping and PID-controller approaches.</p>","PeriodicalId":16235,"journal":{"name":"Journal of Mechanical Science and Technology","volume":"2 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Mechanical Science and Technology","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s12206-024-0837-y","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 0

Abstract

In order to suppress the influence of uncertain disturbances on the trajectory tracking of hydraulic manipulator, a composite control strategy for the cutting electro-hydraulic driving system (CEHDS) of the tunneling robot is presented, which synthesizes the advantages of neural networks technique, recursive backstepping and adaptive control theory. The Lagrangian model with actuator dynamics is derived based on the practical tunneling robot. The back-stepping method is utilized for the strictly feedback state-space model. To address the matched and unmatched lumped uncertainties, the radial-basis-function neural networks (RBFNNs) are employed to approximate the unmatched term which contains the nonlinear friction torque and external cutting load in the mechanical subsystem. The nonlinear disturbance observer (NDOB) is utilized to estimate the matched lumped uncertainty in the hydraulic subsystem. Simultaneously, the adaptive robust mechanism is proposed to compensate the residual disturbances. Based on the Lyapunov theorem, the stability and the bounded tracking error of the CEHDS are obtained. The simulation and experimental results validate the effectiveness of the proposed method in comparison with the common backstepping and PID-controller approaches.

基于扰动补偿的 2-DOF 电液隧道机器人鲁棒后退控制
为了抑制不确定干扰对液压机械手轨迹跟踪的影响,本文综合神经网络技术、递归反步法和自适应控制理论的优点,提出了一种隧道机器人切割电液驱动系统(CEHDS)的复合控制策略。根据实际的隧道机器人推导出了带执行器动力学的拉格朗日模型。严格反馈状态空间模型采用了后步法。为了解决匹配和非匹配的整块不确定性,采用了径向基函数神经网络(RBFNN)来近似非匹配项,其中包含机械子系统中的非线性摩擦力矩和外部切削负载。非线性干扰观测器(NDOB)用于估计液压子系统中的匹配块状不确定性。同时,还提出了自适应鲁棒机制来补偿残余干扰。基于 Lyapunov 定理,得到了 CEHDS 的稳定性和有界跟踪误差。仿真和实验结果验证了所提方法与常见的反步态和 PID 控制器方法相比的有效性。
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
Journal of Mechanical Science and Technology
Journal of Mechanical Science and Technology 工程技术-工程:机械
CiteScore
2.90
自引率
6.20%
发文量
517
审稿时长
7.7 months
期刊介绍: The aim of the Journal of Mechanical Science and Technology is to provide an international forum for the publication and dissemination of original work that contributes to the understanding of the main and related disciplines of mechanical engineering, either empirical or theoretical. The Journal covers the whole spectrum of mechanical engineering, which includes, but is not limited to, Materials and Design Engineering, Production Engineering and Fusion Technology, Dynamics, Vibration and Control, Thermal Engineering and Fluids Engineering. Manuscripts may fall into several categories including full articles, solicited reviews or commentary, and unsolicited reviews or commentary related to the core of mechanical engineering.
×
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