Estimation-based iterative learning control (ILC) is applied to a parallel kinematic manipulator known as the Gantry-Tau parallel robot. The system represents a control problem where measurements of the controlled variables are not available. The main idea is to use estimates of the controlled variables in the ILC algorithm, and in the paper this approach is evaluated experimentally on the Gantry-Tau robot. The experimental results show that an ILC algorithm using estimates of the tool position gives a considerable improvement of the control performance. The tool position estimate is obtained by fusing measurements of the actuator angular positions with measurements of the tool path acceleration using a complementary filter. ; Funding Agencies|ELLIIT, Excellence Center at Linkoping - Lund in Information Technology; LCCC Linnaeus Center at Lund University; Vinnovas Industry Excellence Center LINK-SIC at Linkoping University
Estimation-based ILC applied to a parallel kinematic robot
2014-01-01
ISI:000345728700001
Article (Journal)
Electronic Resource
English
DDC: | 629 |
Modal kinematic analysis of a parallel kinematic robot with low-stiffness transmissions
BASE | 2021
|Kinematic calibration of a wire-actuated parallel robot
Online Contents | 2007
|Complete Inverse Geometric Model Computation of the Quattro Parallel Kinematic Robot
Springer Verlag | 2022
|