Details
| Original language | English |
|---|---|
| Title of host publication | 2018 IEEE 14th International Conference on Automation Science and Engineering, CASE 2018 |
| Publisher | IEEE Computer Society |
| Pages | 408-413 |
| Number of pages | 6 |
| ISBN (electronic) | 9781538635933 |
| Publication status | Published - 2018 |
| Event | 14th IEEE International Conference on Automation Science and Engineering, CASE 2018 - Munich, Germany Duration: 20 Aug 2018 → 24 Aug 2018 |
Publication series
| Name | IEEE International Conference on Automation Science and Engineering |
|---|---|
| ISSN (Print) | 2161-8070 |
| ISSN (electronic) | 2161-8089 |
Abstract
Reducing the energy consumption is a major concern in industrial production systems. One approach is recuperating the braking energy of robot axes. Ideally, their acceleration and deceleration phases should be synchronized so that the braking energy of one axis can be reused directly to accelerate another. This requires a detailed alignment of the axes' trajectories, but also a careful design of the overall discrete control. Finding an optimal control strategy manually, however, is difficult, as also many functional and safety requirements must be considered. We therefore propose an automated methodology that consists of three parts: (1) A scenario-based language to flexibly specify the discrete production system behavior, (2) an automated procedure to synthesize optimal control strategies from such specifications, including PLC code generation, and (3) a procedure for the detailed trajectory optimization. We describe the methodology, focusing on parts (1) and (2) in this paper, and present tool support and evaluation results.
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
- Engineering(all)
- Electrical and Electronic Engineering
Sustainable Development Goals
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2018 IEEE 14th International Conference on Automation Science and Engineering, CASE 2018. IEEE Computer Society, 2018. p. 408-413 8560544 (IEEE International Conference on Automation Science and Engineering).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Specifying and Synthesizing Energy-Efficient Production System Controllers that Exploit Braking Energy Recuperation
AU - Gritzner, Daniel
AU - Knöchelmann, Elias
AU - Greenyer, Joel
AU - Eggers, Kai
AU - Tappe, Svenja
AU - Ortmaier, Tobias
N1 - Funding information: *This research is funded by the DFG project EffiSynth.
PY - 2018
Y1 - 2018
N2 - Reducing the energy consumption is a major concern in industrial production systems. One approach is recuperating the braking energy of robot axes. Ideally, their acceleration and deceleration phases should be synchronized so that the braking energy of one axis can be reused directly to accelerate another. This requires a detailed alignment of the axes' trajectories, but also a careful design of the overall discrete control. Finding an optimal control strategy manually, however, is difficult, as also many functional and safety requirements must be considered. We therefore propose an automated methodology that consists of three parts: (1) A scenario-based language to flexibly specify the discrete production system behavior, (2) an automated procedure to synthesize optimal control strategies from such specifications, including PLC code generation, and (3) a procedure for the detailed trajectory optimization. We describe the methodology, focusing on parts (1) and (2) in this paper, and present tool support and evaluation results.
AB - Reducing the energy consumption is a major concern in industrial production systems. One approach is recuperating the braking energy of robot axes. Ideally, their acceleration and deceleration phases should be synchronized so that the braking energy of one axis can be reused directly to accelerate another. This requires a detailed alignment of the axes' trajectories, but also a careful design of the overall discrete control. Finding an optimal control strategy manually, however, is difficult, as also many functional and safety requirements must be considered. We therefore propose an automated methodology that consists of three parts: (1) A scenario-based language to flexibly specify the discrete production system behavior, (2) an automated procedure to synthesize optimal control strategies from such specifications, including PLC code generation, and (3) a procedure for the detailed trajectory optimization. We describe the methodology, focusing on parts (1) and (2) in this paper, and present tool support and evaluation results.
UR - http://www.scopus.com/inward/record.url?scp=85059974403&partnerID=8YFLogxK
U2 - 10.15488/10363
DO - 10.15488/10363
M3 - Conference contribution
AN - SCOPUS:85059974403
T3 - IEEE International Conference on Automation Science and Engineering
SP - 408
EP - 413
BT - 2018 IEEE 14th International Conference on Automation Science and Engineering, CASE 2018
PB - IEEE Computer Society
T2 - 14th IEEE International Conference on Automation Science and Engineering, CASE 2018
Y2 - 20 August 2018 through 24 August 2018
ER -