Experimental results for output feedback adaptive robot control

Abstract

The author has granted a non exclusive license allowing Library and Archives Canada to reproduce, publish, archive, preserve, conserve, communicate to the public by telecommunication or on the Internet, loan, distribute and sell theses worldwide, for commercial or non commercial purposes, in microform, paper, electronic and/or any other formats. AVIS: L'auteur a accorde une licence non exclusive permettant a la Bibliotheque et Archives Canada de reproduire, publier, archiver, sauvegarder, conserver, transmettre au public par telecommunication ou par I'lnternet, preter, distribuer et vendre des theses partout dans le monde, a des fins commerciales ou autres, sur support microforme, papier, electronique et/ou autres formats. A bstract ii A cknow ledgem ents iii C ontents iv List o f Figures vii Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.

Uniform Global Asymptotic Stability of an Adaptive Output Feedback Tracking Controller for Robot Manipulators*

“…It is well known that measurement of joint velocities in a robot manipulator frequently produces noisy signals, so much that its use in a controller may not be feasible (see Daly and Schwarz (2006)). To overcome this problem, some output feedback controllers have been proposed.…”

Velocity Estimation of Robot Manipulators: An Experimental Comparison

“…Simulative comparisons of derivative filters for discrete position measurements showed that no approach works best for all velocity profiles [4]- [6]. In the simulative comparison in [7], an extended Kalman filter, a nonlinear high-gain observer, and a linear observer have been compared considering their position estimation error and tracking error on a two degrees-offreedom (DOF) robot. The authors in [8], [9] experimentally compare the tracking error of different tracking controllers using linear high-gain observers.…”

Continuous output‐feedback finite‐time control for a class of second‐order nonlinear systems with disturbances

“…For example, in some mechanical systems, velocity signals are generally immeasurable. Despite being obtained by differentiating the position signals from encoders or resolvers, velocity signals are often contaminated by noise . One solution is to reconstruct system states and then apply the estimated signals to the control loop.…”