Abstract
Natural Orifice Transluminal Endoscopic Surgery (NOTES) is a method that allows for performing complex operations via natural orifices without skin incisions. Its main tool is a flexible endoscope. Cable-conduit mechanism (CCM) or tendon-sheath Mechanism (TSM) is often used in NOTES because of its simplicity, safety in design, and easy transmission. Nonlinearities between the cable and the conduit pose challenges in the motion control of the NOTES system. It is very difficult to achieve the precise position of robotic arms when the system is inside a human's body. This paper presents new approaches to model and control a pair of CCMs (TSMs) used in NOTES system. To deal with the change of cable-conduit configurations during its operation, two control schemes are proposed: (i) an updated table with offline backlash hysteresis learning is constructed. In this case, a simple computation of the direct inverse backlash hysteresis model is introduced without using output feedback for compensation; and (ii) an online estimation of the backlash hysteresis profile under the assumption of availability of output feedback. In this case, adaptive control laws are used to deal with the change of the endoscope configuration. The proposed model and compensation control schemes are experimentally validated using a prototype of a single-DOF-Master-Slave system, which consists of a master console, a telesurgical workstation, and a slave manipulator. The results show that the proposed model and the control schemes improve the tracking performances of the system.
Original language | English |
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Pages (from-to) | 197-207 |
Number of pages | 11 |
Journal | Robotics and Computer-Integrated Manufacturing |
Volume | 37 |
DOIs | |
Publication status | Published - Feb 1 2016 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2015 Elsevier Ltd. All rights reserved.
ASJC Scopus Subject Areas
- Control and Systems Engineering
- Software
- General Mathematics
- Computer Science Applications
- Industrial and Manufacturing Engineering
Keywords
- Adaptive control
- Cable-conduit mechanism
- Feedforward control
- Flexible endoscope
- Master-Slave system