Abstract
This paper proposes to apply the fuzzy model reference learning control method based on the guide control to the collaborative human-machine dragging process of the surgical robot. Variable damping coefficient adjustment parameter rules for fuzzy conductance controllers are trained by an offline learning mechanism in order to achieve the best human-machine interaction control effect. The surgical risk caused by the doctor's misoperation is lowered. Through the simulation experiment results, the speed curve tracking error is reduced by 70%. Trajectory curve tracking error is reduced by 57%. The both results prove that the strategy can reduce the error of the surgical robot and ensure the safety of robotic surgical operation.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Frontiers in Engineering Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
