Details
| Original language | English |
|---|---|
| Title of host publication | Informatics in Control, Automation and Robotics |
| Subtitle of host publication | 14th International Conference, ICINCO 2017 Madrid, Spain, July 26-28, 2017 Revised Selected Papers |
| Editors | Kurosh Madani, Oleg Gusikhin |
| Place of Publication | Cham |
| Publisher | Springer Verlag |
| Chapter | 339 |
| Pages | 339-354 |
| Number of pages | 16 |
| ISBN (electronic) | 9783030112929 |
| ISBN (print) | 9783030112912 |
| Publication status | Published - 18 Apr 2019 |
| 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 | Lecture Notes in Electrical Engineering |
|---|---|
| Volume | 495 |
| ISSN (Print) | 1876-1100 |
| ISSN (electronic) | 1876-1119 |
Abstract
This work proposes two approaches to automatic tuning of PID position controllers based on different global optimization strategies. The chosen optimization algorithms are PSO and MOPSO, i. e. the problem is handled as a single objective problem in the first implementation and as a multiobjective problem in the second one. The auto-tuning is performed without assuming any previous knowledge of the robot dynamics. The objective functions are evaluated depending on real movements of the robot. Therefore, constraints guaranteeing safe and stable robot motion are necessary, namely: a maximum joint torque constraint, a maximum position error constraint and an oscillation constraint. Because of the practical nature of the problem in hand, constraints must be observed online. This requires adaptation of the optimization algorithm for reliable observance of the constraints without affecting the convergence rate of the objective function. Finally, Experimental results of a 3-DOF robot for different trajectories and with different settings show the validity of the two approaches and demonstrate the advantages and disadvantages of every method.
Keywords
- Automatic tuning, MOPSO, PID control, PSO, Robotic manipulators
ASJC Scopus subject areas
- Engineering(all)
- Industrial and Manufacturing Engineering
Cite this
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Informatics in Control, Automation and Robotics: 14th International Conference, ICINCO 2017 Madrid, Spain, July 26-28, 2017 Revised Selected Papers. ed. / Kurosh Madani; Oleg Gusikhin. Cham: Springer Verlag, 2019. p. 339-354 (Lecture Notes in Electrical Engineering; Vol. 495).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Auto-tuning of PID controllers for robotic manipulators using PSO and MOPSO
AU - Zidan, Ahmed
AU - Tappe, Svenja
AU - Ortmaier, Tobias
PY - 2019/4/18
Y1 - 2019/4/18
N2 - This work proposes two approaches to automatic tuning of PID position controllers based on different global optimization strategies. The chosen optimization algorithms are PSO and MOPSO, i. e. the problem is handled as a single objective problem in the first implementation and as a multiobjective problem in the second one. The auto-tuning is performed without assuming any previous knowledge of the robot dynamics. The objective functions are evaluated depending on real movements of the robot. Therefore, constraints guaranteeing safe and stable robot motion are necessary, namely: a maximum joint torque constraint, a maximum position error constraint and an oscillation constraint. Because of the practical nature of the problem in hand, constraints must be observed online. This requires adaptation of the optimization algorithm for reliable observance of the constraints without affecting the convergence rate of the objective function. Finally, Experimental results of a 3-DOF robot for different trajectories and with different settings show the validity of the two approaches and demonstrate the advantages and disadvantages of every method.
AB - This work proposes two approaches to automatic tuning of PID position controllers based on different global optimization strategies. The chosen optimization algorithms are PSO and MOPSO, i. e. the problem is handled as a single objective problem in the first implementation and as a multiobjective problem in the second one. The auto-tuning is performed without assuming any previous knowledge of the robot dynamics. The objective functions are evaluated depending on real movements of the robot. Therefore, constraints guaranteeing safe and stable robot motion are necessary, namely: a maximum joint torque constraint, a maximum position error constraint and an oscillation constraint. Because of the practical nature of the problem in hand, constraints must be observed online. This requires adaptation of the optimization algorithm for reliable observance of the constraints without affecting the convergence rate of the objective function. Finally, Experimental results of a 3-DOF robot for different trajectories and with different settings show the validity of the two approaches and demonstrate the advantages and disadvantages of every method.
KW - Automatic tuning
KW - MOPSO
KW - PID control
KW - PSO
KW - Robotic manipulators
UR - http://www.scopus.com/inward/record.url?scp=85065506119&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-11292-9_17
DO - 10.1007/978-3-030-11292-9_17
M3 - Conference contribution
AN - SCOPUS:85065506119
SN - 9783030112912
T3 - Lecture Notes in Electrical Engineering
SP - 339
EP - 354
BT - Informatics in Control, Automation and Robotics
A2 - Madani, Kurosh
A2 - Gusikhin, Oleg
PB - Springer Verlag
CY - Cham
T2 - 14th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2017
Y2 - 26 July 2017 through 28 July 2017
ER -