Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/105802
Title: Nonlinear modeling and parameter identification of dynamic friction model in tendon sheath for flexible endoscopic systems
Authors: Thanh Nho, Do
Tjahjowidodo, Tegoeh
Lau, Michael Wai Shing
Phee, Soo Jay
Keywords: DRNTU::Engineering::Mechanical engineering::Machine design and construction
Issue Date: 2013
Source: T. N. Do, T. Tjahjowidodo, Lau. M. W. S., & Phee. S. J. (2013). Nonlinear modeling and parameter identification of dynamic friction model in tendon sheath for flexible endoscopic systems. Proceedings of the 10th International Conference on Informatics in Control, Automation and Robotics (ICINCO), Reykjavik, Iceland, 5-10.
Conference: 10th International Conference on Informatics in Control, Automation and Robotics (ICINCO)
Abstract: Minimally Invasive Surgery (MIS) has established a revolution in surgical communities, with its many advantages over open surgery. The need of more simplicity and high maneuverability makes the tendon sheath a very suitable mechanism in flexible endoscopic systems. Due to the restriction on size constraints and sterilization problems, traditional sensors cannot be mounted on the tool tips of a slave manipulator. Moreover, in the presence of nonlinear friction and hysteresis between the tendon and the sheath, it is extremely difficult to control the precise motion and sense the force during the operation. This paper proposes a new dynamic friction model to estimate the force at the end effector for the tendon sheath mechanism. The proposed friction model can adapt with any initial pretension of the tendon and any configuration of the sheath. The nonlinearities in both sliding and presliding regimes can be captured by using an internal state variable and functions dependent velocity and acceleration. A specific setup has been designed in order to measure the friction force between the tendon and the sheath. Finally, the validity of the identified model is confirmed by a good agreement of its prediction and experimental data.
URI: https://hdl.handle.net/10356/105802
http://hdl.handle.net/10220/20900
DOI: 10.5220/0004409800050010
Schools: School of Mechanical and Aerospace Engineering 
Research Centres: Robotics Research Centre 
Rights: © 2013 Science and Technology Publications(SCITEPRESS). This paper was published in Proceedings of the 10th International Conference on Informatics in Control, Automation and Robotics (ICINCO) and is made available as an electronic reprint (preprint) with permission of Science and Technology Publications(SCITEPRESS). The paper can be found at the following official DOI: [http://dx.doi.org/10.5220/0004409800050010]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Conference Papers

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