Estimation-based ILC applied to a parallel kinematic robot
Author
Summary, in English
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. (C) 2014 Elsevier Ltd. All rights reserved.
Department/s
Publishing year
2014
Language
English
Pages
1-9
Publication/Series
Control Engineering Practice
Volume
33
Links
Document type
Journal article
Publisher
Elsevier
Topic
- Robotics
- Control Engineering
Keywords
- Iterative methods
- Learning control
- Robotic manipulator
- Estimation algorithm
- Performance evaluation
Status
Published
Project
- LCCC
Research group
- ELLIIT
- LCCC
- LUCAS
ISBN/ISSN/Other
- ISSN: 0967-0661