For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
6
views
36
references
 Top references
cited by
0
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
0 collections
    0
    shares
      46
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Adaptive fuzzy control for tendon-sheath actuated bending-tip system with unknown friction for robotic flexible endoscope

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Introduction

          The tendon-sheath actuated bending-tip system (TAB) has been widely applied to long-distance transmission scenes due to its high maneuverability, safety, and compliance, such as in exoskeleton robots, rescue robots, and surgical robots design. Due to the suitability of operation in a narrow or tortuous environment, TAB has demonstrated great application potential in the area of minimally invasive surgery. However, TAB involves highly non-linear behavior due to hysteresis, creepage, and non-linear friction existing on the tendon routing, which is an enormous challenge for accurate control.

          Methods

          Considering the difficulties in the precise modeling of non-linearity friction, this paper proposes a novel fuzzy control scheme for the Euler-Lagrange dynamics model of TAB for achieving tracking performance and providing accurate friction compensation. Finally, the asymptotic stability of the closed-loop system is proved theoretically and the effectiveness of the controller is verified by numerical simulation carried out in MATLAB/Simulink.

          Results

          The desired angle can be reached quickly within 3 s by adopting the proposed controller without overshoot or oscillation in Tracking Experiment, demonstrating the regulation performance of the proposed control scheme. The proposed method still achieves the desired trajectory rapidly and accurately without steady-state errors in Varying-friction Experiment. The angle errors generated by external disturbances are < 1 deg under the proposed controller, which returns to zero in 2 s in Anti-disturbance Experiment. In contrast, comparative controllers take more time to be steady and are accompanied by oscillating and residual errors in all experiments.

          Discussion

          The proposed method is model-free control and has no strict requirement for the dynamics model and friction model. It is proved that advanced tracking performance and real-time response can be guaranteed under the presence of unknown bounded non-linear friction and time-varying non-linear dynamics.

          Related collections

          Most cited references36

          • Record: found
          • Abstract: not found
          • Article: not found

          Continuum Robots for Medical Applications: A Survey

          Jessica Burgner-Kahrs, D Caleb Rucker, Howie Choset (2015)
          Article 0 comments Cited 176 times – based on 0 reviews     Review now
            Bookmark
            • Record: found
            • Abstract: not found
            • Book: not found

            Adaptive fuzzy systems and control: Design and stability analysis

            Wang L.-X., L-X Wang, L Wang … (1994)
            Book 0 comments Cited 18 times – based on 0 reviews
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Adaptive control for enhancing tracking performances of flexible tendon–sheath mechanism in natural orifice transluminal endoscopic surgery (NOTES)

              T.N. Do, T. Tjahjowidodo, M.W.S. Lau … (2015)
              Article 0 comments Cited 15 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Contributors
                Fan Ren: URI : http://loop.frontiersin.org/people/2541338/overviewRole: Role: Role: Role: Role:
                Xiangyu Wang: URI : http://loop.frontiersin.org/people/2417995/overviewRole: Role: Role: Role:
                Ningbo Yu: URI : http://loop.frontiersin.org/people/487196/overviewRole: Role:
                Jianda Han: Role: Role:
                Journal
                Journal ID (nlm-ta): Front Neurosci
                Journal ID (iso-abbrev): Front Neurosci
                Journal ID (publisher-id): Front. Neurosci.
                Title: Frontiers in Neuroscience
                Publisher: Frontiers Media S.A.
                ISSN (Print): 1662-4548
                ISSN (Electronic): 1662-453X
                Publication date (Electronic): 26 March 2024
                Publication date Collection: 2024
                Volume: 18
                Electronic Location Identifier: 1330634
                Affiliations
                [1] 1The Tianjin Key Laboratory of Intelligent Robotics, College of Artificial Intelligence, Institute of Robotics and Automatic Information Systems, Nankai University , Tianjin, China
                [2] 2The Institute of Intelligence Technology and Robotic Systems, Shenzhen Research Institute of Nankai University , Shenzhen, China
                Author notes

                Edited by: Yingbai Hu, The Chinese University of Hong Kong, China

                Reviewed by: Rong Song, Sun Yat-sen University, China

                Yisen Huang, The Chinese University of Hong Kong, China

                *Correspondence: Xiangyu Wang wangxyu@ 123456nankai.edu.cn

                This article was submitted to Original Research Article, a section of the journal Frontiers in Neuroscience

                Article
                DOI: 10.3389/fnins.2024.1330634
                PMC ID: 11002250
                PubMed ID: 38595970
                SO-VID: e127f576-cf2e-4fa9-9bce-d01c8a326e15
                Copyright © Copyright © 2024 Ren, Wang, Yu and Han.
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                Date received : 31 October 2023
                Date accepted : 11 March 2024
                Page count
                Figures: 8, Tables: 1, Equations: 38, References: 36, Pages: 12, Words: 6314
                Funding
                The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This work was supported by National Key R&D Program of China (Grant No. 2022YFB4702800), National Natural Science Foundation of China (Grant No. 62303248), Guanddong Basic and Applied Basic Research Foundation (Grant Nos. 2024A1515010102 and 2023A1515110678), and China Postdoctoral Science Foundation Funded Project (Grant No. 2023M731804).
                Categories
                Subject: Neuroscience
                Subject: Original Research

                ScienceOpen disciplines: Neurosciences
                Keywords: tendon-sheath mechanism,fuzzy control,friction compensation,robust control,robotic flexible endoscope
                Data availability:
                ScienceOpen disciplines: Neurosciences
                Keywords: tendon-sheath mechanism, fuzzy control, friction compensation, robust control, robotic flexible endoscope

                Comments

                Comment on this article