{"title":"High-Fidelity Virtual Model for Industrial Robot Control Under Uncertain and Disturbed Scenarios: A Comparative Study on the UR5e","authors":"Heni Belgacem;Mohammad Abuabiah;Inés Chihi","doi":"10.1109/ACCESS.2025.3604653","DOIUrl":null,"url":null,"abstract":"Robust control of industrial manipulators under real-world uncertainties is critical for reliable automation. This work presents a comprehensive framework for modeling, control, and performance evaluation of the UR5e robotic manipulator. High-fidelity kinematic and dynamic models are developed and validated against experimental data to create a realistic virtual environment. Four control strategies, including Computed Torque Control, Proportional Integral Derivative, Sliding Mode Control, and Nonlinear Model Predictive Control are implemented and systematically compared. The comparison considers tracking accuracy, robustness, energy efficiency, and computational demand under nominal conditions as well as in the presence of external disturbances, sensor noise, and model uncertainties. Sliding Mode Control demonstrates consistent tracking under disturbances, Nonlinear Model Predictive Control achieves reduced energy consumption with smooth motion profiles, Computed Torque Control provides balanced accuracy and response, and Proportional Integral Derivative performs effectively under low-disturbance conditions. The methodology provides a validated simulation platform for benchmarking robotic control strategies and supports data-driven selection of controllers for industrial applications.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"152063-152089"},"PeriodicalIF":3.6000,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11145441","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Access","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/11145441/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Robust control of industrial manipulators under real-world uncertainties is critical for reliable automation. This work presents a comprehensive framework for modeling, control, and performance evaluation of the UR5e robotic manipulator. High-fidelity kinematic and dynamic models are developed and validated against experimental data to create a realistic virtual environment. Four control strategies, including Computed Torque Control, Proportional Integral Derivative, Sliding Mode Control, and Nonlinear Model Predictive Control are implemented and systematically compared. The comparison considers tracking accuracy, robustness, energy efficiency, and computational demand under nominal conditions as well as in the presence of external disturbances, sensor noise, and model uncertainties. Sliding Mode Control demonstrates consistent tracking under disturbances, Nonlinear Model Predictive Control achieves reduced energy consumption with smooth motion profiles, Computed Torque Control provides balanced accuracy and response, and Proportional Integral Derivative performs effectively under low-disturbance conditions. The methodology provides a validated simulation platform for benchmarking robotic control strategies and supports data-driven selection of controllers for industrial applications.
IEEE AccessCOMPUTER SCIENCE, INFORMATION SYSTEMSENGIN-ENGINEERING, ELECTRICAL & ELECTRONIC
CiteScore
9.80
自引率
7.70%
发文量
6673
审稿时长
6 weeks
期刊介绍:
IEEE Access® is a multidisciplinary, open access (OA), applications-oriented, all-electronic archival journal that continuously presents the results of original research or development across all of IEEE''s fields of interest.
IEEE Access will publish articles that are of high interest to readers, original, technically correct, and clearly presented. Supported by author publication charges (APC), its hallmarks are a rapid peer review and publication process with open access to all readers. Unlike IEEE''s traditional Transactions or Journals, reviews are "binary", in that reviewers will either Accept or Reject an article in the form it is submitted in order to achieve rapid turnaround. Especially encouraged are submissions on:
Multidisciplinary topics, or applications-oriented articles and negative results that do not fit within the scope of IEEE''s traditional journals.
Practical articles discussing new experiments or measurement techniques, interesting solutions to engineering.
Development of new or improved fabrication or manufacturing techniques.
Reviews or survey articles of new or evolving fields oriented to assist others in understanding the new area.