Details
| Original language | English |
|---|---|
| Title of host publication | ICINCO 2017 - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics |
| Editors | Oleg Gusikhin, Kurosh Madani |
| Pages | 34-40 |
| Number of pages | 7 |
| ISBN (electronic) | 9789897582646 |
| Publication status | Published - 2017 |
| Event | 14th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2017 - Madrid, Spain Duration: 26 Jul 2017 → 28 Jul 2017 |
Publication series
| Name | ICINCO 2017 - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics |
|---|---|
| Volume | 2 |
Abstract
An auto-tuning method of PD controllers for robotic manipulators is proposed. This method suggests a practical implementation of the particle swarm optimization technique in order to find optimal gain values achieving the best tracking of a predefined position trajectory. For this purpose, The integral of the absolute error IAE is used as a cost function for the optimization algorithm. The optimization is achieved by performing the desired movement of the robot iteratively and evaluating the cost function for every iteration. Therefor, the necessary constraints that guarantee a safe and stable movement of the robot are defined, which are: A maximum joint torque constraint, a maximum position error constraint and an oscillation constraint. A constraint handling approach is suggested for the optimization algorithm in order to adapt it to the problem in hand. Finally, the efficiency of the proposed method is verified through a practical experiment on a real robot.
Keywords
- Automatic tuning, Particle swarm optimization, Pd control, Robotic manipulators
ASJC Scopus subject areas
- Computer Science(all)
- Computer Vision and Pattern Recognition
- Engineering(all)
- Control and Systems Engineering
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ICINCO 2017 - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics. ed. / Oleg Gusikhin; Kurosh Madani. 2017. p. 34-40 (ICINCO 2017 - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics; Vol. 2).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - A Practical approach for the auto-tuning of PD controllers for robotic manipulators using particle swarm optimization
AU - Zidan, Ahmed
AU - Kotlarski, Jens
AU - Ortmaier, Tobias
N1 - Publisher Copyright: © 2017 by SCITEPRESS - Science and Technology Publications, Lda. All Rights Reserved. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2017
Y1 - 2017
N2 - An auto-tuning method of PD controllers for robotic manipulators is proposed. This method suggests a practical implementation of the particle swarm optimization technique in order to find optimal gain values achieving the best tracking of a predefined position trajectory. For this purpose, The integral of the absolute error IAE is used as a cost function for the optimization algorithm. The optimization is achieved by performing the desired movement of the robot iteratively and evaluating the cost function for every iteration. Therefor, the necessary constraints that guarantee a safe and stable movement of the robot are defined, which are: A maximum joint torque constraint, a maximum position error constraint and an oscillation constraint. A constraint handling approach is suggested for the optimization algorithm in order to adapt it to the problem in hand. Finally, the efficiency of the proposed method is verified through a practical experiment on a real robot.
AB - An auto-tuning method of PD controllers for robotic manipulators is proposed. This method suggests a practical implementation of the particle swarm optimization technique in order to find optimal gain values achieving the best tracking of a predefined position trajectory. For this purpose, The integral of the absolute error IAE is used as a cost function for the optimization algorithm. The optimization is achieved by performing the desired movement of the robot iteratively and evaluating the cost function for every iteration. Therefor, the necessary constraints that guarantee a safe and stable movement of the robot are defined, which are: A maximum joint torque constraint, a maximum position error constraint and an oscillation constraint. A constraint handling approach is suggested for the optimization algorithm in order to adapt it to the problem in hand. Finally, the efficiency of the proposed method is verified through a practical experiment on a real robot.
KW - Automatic tuning
KW - Particle swarm optimization
KW - Pd control
KW - Robotic manipulators
UR - http://www.scopus.com/inward/record.url?scp=85029391993&partnerID=8YFLogxK
U2 - 10.5220/0006419700340040
DO - 10.5220/0006419700340040
M3 - Conference contribution
AN - SCOPUS:85029391993
T3 - ICINCO 2017 - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics
SP - 34
EP - 40
BT - ICINCO 2017 - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics
A2 - Gusikhin, Oleg
A2 - Madani, Kurosh
T2 - 14th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2017
Y2 - 26 July 2017 through 28 July 2017
ER -