Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 223-247 |
| Seitenumfang | 25 |
| Fachzeitschrift | Journal of Control and Decision |
| Jahrgang | 3 |
| Ausgabenummer | 4 |
| Publikationsstatus | Veröffentlicht - 1 Okt. 2016 |
Abstract
Automated production systems typically comprise numerous electrical servo drives, many of which conduct positioning motions, e.g. for handling or manipulation tasks. The power electronics of modern multi-axis systems often comprise coupled DC-links, enabling for internal exchange of recuperative brake energy. However, the motion sequences of manipulators are often commanded at maximum dynamics for minimum time motion, neglecting possible optimization potential, e.g. available idle time, leading to inefficient energy management. A robust trajectory optimization approach based on the particle swarm algorithm and well-established path planning methods is presented for the adaption of multi-axis positioning tasks with only two parameters per axis and positioning motion during system run-time. Experimental results prove that, depending on the positioning task and chosen optimization constraints, energy demands are distinctly reduced. The approach is applicable to diverse multi-axis configurations and enables for considerable energy savings without additional hardware invest.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Steuerungs- und Systemtechnik
- Informatik (insg.)
- Signalverarbeitung
- Informatik (insg.)
- Information systems
- Informatik (insg.)
- Mensch-Maschine-Interaktion
- Informatik (insg.)
- Computernetzwerke und -kommunikation
- Mathematik (insg.)
- Steuerung und Optimierung
- Informatik (insg.)
- Artificial intelligence
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in: Journal of Control and Decision, Jahrgang 3, Nr. 4, 01.10.2016, S. 223-247.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - A concurrent optimization approach for energy efficient multiple axis positioning tasks
AU - Hansen, Christian
AU - Kotlarski, Jens
AU - Ortmaier, Tobias
N1 - Funding information: This work was supported by the German Research Foundation (DFG) [grant number OR196/4-2].
PY - 2016/10/1
Y1 - 2016/10/1
N2 - Automated production systems typically comprise numerous electrical servo drives, many of which conduct positioning motions, e.g. for handling or manipulation tasks. The power electronics of modern multi-axis systems often comprise coupled DC-links, enabling for internal exchange of recuperative brake energy. However, the motion sequences of manipulators are often commanded at maximum dynamics for minimum time motion, neglecting possible optimization potential, e.g. available idle time, leading to inefficient energy management. A robust trajectory optimization approach based on the particle swarm algorithm and well-established path planning methods is presented for the adaption of multi-axis positioning tasks with only two parameters per axis and positioning motion during system run-time. Experimental results prove that, depending on the positioning task and chosen optimization constraints, energy demands are distinctly reduced. The approach is applicable to diverse multi-axis configurations and enables for considerable energy savings without additional hardware invest.
AB - Automated production systems typically comprise numerous electrical servo drives, many of which conduct positioning motions, e.g. for handling or manipulation tasks. The power electronics of modern multi-axis systems often comprise coupled DC-links, enabling for internal exchange of recuperative brake energy. However, the motion sequences of manipulators are often commanded at maximum dynamics for minimum time motion, neglecting possible optimization potential, e.g. available idle time, leading to inefficient energy management. A robust trajectory optimization approach based on the particle swarm algorithm and well-established path planning methods is presented for the adaption of multi-axis positioning tasks with only two parameters per axis and positioning motion during system run-time. Experimental results prove that, depending on the positioning task and chosen optimization constraints, energy demands are distinctly reduced. The approach is applicable to diverse multi-axis configurations and enables for considerable energy savings without additional hardware invest.
KW - electrical servo drive
KW - energy efficient control
KW - Multiple axis systems
KW - positioning tasks
KW - trajectory optimization
UR - http://www.scopus.com/inward/record.url?scp=85051656427&partnerID=8YFLogxK
U2 - 10.1080/23307706.2016.1208548
DO - 10.1080/23307706.2016.1208548
M3 - Article
AN - SCOPUS:85051656427
VL - 3
SP - 223
EP - 247
JO - Journal of Control and Decision
JF - Journal of Control and Decision
SN - 2330-7706
IS - 4
ER -