JOURNAL ARTICLE
RESEARCH SUPPORT, NON-U.S. GOV'T
Add like
Add dislike
Add to saved papers

Time-scale separation of a class of robust PD-type tracking controllers for robot manipulators.

In this paper, the trajectory tracking control of robot manipulators is studied from the theoretical and practical point of view. By using the theory of singularly perturbed systems, a class of PD-type robust controllers is introduced. Our analysis departs from parameterizing the proportional and derivative gains with a perturbing parameter. We prove that the smaller the value of perturbing parameter, the smaller the ultimate bound of the joint position tracking error. Derived from the introduced analysis, two forms of extending the proposed class of controllers are discussed. In one, error-varying PD gains are considered while in the another one, a dynamic extension to avoid joint velocity measurements is incorporated. An experimental study in a planar two degrees-of-freedom direct-drive robot is also presented. Under similar implementation conditions, four controllers are tested. The best performance is obtained for a nonlinear PD controller derived from the proposed class of controllers.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

Related Resources

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app