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Iterative Learning Control with Application to Robotics

Scalamogna, Domenico (2001) In MSc Theses
Department of Automatic Control
Abstract
Many machines and robots working today in factories are programmed to perform the same task repeatedly.
By observing the tracking error in each iteration of the same task it becomes clear that it is actually repetitive, even though disturbances from noise and possibly sligthly changing friction dynamics affect the response.
The idea of Iterative learning Control D ILC E is to use the knowledge from the previous iterations of the same task to reduce the tracking error the next time the task is performed. ILC utilizes the tracking error knowledge from the previous iteration to change the input signal to the system. In the thesis ILC is applied to an ABB Irb-2000 industrial robot. Using ILC the tracking error on the motor side has been... (More)
Many machines and robots working today in factories are programmed to perform the same task repeatedly.
By observing the tracking error in each iteration of the same task it becomes clear that it is actually repetitive, even though disturbances from noise and possibly sligthly changing friction dynamics affect the response.
The idea of Iterative learning Control D ILC E is to use the knowledge from the previous iterations of the same task to reduce the tracking error the next time the task is performed. ILC utilizes the tracking error knowledge from the previous iteration to change the input signal to the system. In the thesis ILC is applied to an ABB Irb-2000 industrial robot. Using ILC the tracking error on the motor side has been reduced without changing the internal structure or any parameter in the robot controller.
Three different ILC algorithms are considered in the thesis. Also some important theorems about ILC stability are taken into account. Two of these three ILC algorithms have been applied to the robot to improve the tracking of desired trajectories.
ILC has also been used in order to improve the robot motion of an open container with liquid. The purpose was to shorten the motion time of the package transfer with control of the slosh inside. (Less)
Please use this url to cite or link to this publication:
author
Scalamogna, Domenico
supervisor
organization
year
type
H3 - Professional qualifications (4 Years - )
subject
publication/series
MSc Theses
report number
TFRT-5672
ISSN
0280-5316
language
English
id
8848271
date added to LUP
2016-03-20 11:14:24
date last changed
2016-03-20 11:14:24
@misc{8848271,
  abstract     = {Many machines and robots working today in factories are programmed to perform the same task repeatedly.
By observing the tracking error in each iteration of the same task it becomes clear that it is actually repetitive, even though disturbances from noise and possibly sligthly changing friction dynamics affect the response.
The idea of Iterative learning Control D ILC E is to use the knowledge from the previous iterations of the same task to reduce the tracking error the next time the task is performed. ILC utilizes the tracking error knowledge from the previous iteration to change the input signal to the system. In the thesis ILC is applied to an ABB Irb-2000 industrial robot. Using ILC the tracking error on the motor side has been reduced without changing the internal structure or any parameter in the robot controller.
Three different ILC algorithms are considered in the thesis. Also some important theorems about ILC stability are taken into account. Two of these three ILC algorithms have been applied to the robot to improve the tracking of desired trajectories.
ILC has also been used in order to improve the robot motion of an open container with liquid. The purpose was to shorten the motion time of the package transfer with control of the slosh inside.},
  author       = {Scalamogna, Domenico},
  issn         = {0280-5316},
  language     = {eng},
  note         = {Student Paper},
  series       = {MSc Theses},
  title        = {Iterative Learning Control with Application to Robotics},
  year         = {2001},
}