Energy Optimal Tracking Control with Discrete Fluid Power Systems using Model Predictive Control

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearch

Abstract

For Discrete Displacement Cylinder (DDC) drives the control task lies in choosing force level. Hence, which force level to apply and thereby which pressure level each cylinder chambers shall be connected to. The DDC system is inherently a force system why often a force reference is generated by a tracking controller and translated into a discrete force level in a Force Shifting Algorithm (FSA). In the current paper the tracking controller and the FSA are combined in a Model Predictive Control algorithm solving the tracking problem while minimizing the energy use. Two MPC algorithms are investigated and compared to a PID like tracking controller combined with a FSA. The results indicate that the energy efficiency of position tracking DDC systems may be improved significantly by using the MPC algorithm.
Original languageEnglish
Title of host publicationProceedings of 9th Workshop on Digital Fluid Power, DFP 2017
Number of pages13
PublisherDepartment of Energy Technology, Aalborg University
Publication dateSep 2017
Publication statusPublished - Sep 2017
Event9th Workshop on Digital Fluid Power, DFP 2017 - Aalborg, Denmark
Duration: 7 Sep 20178 Sep 2017

Conference

Conference9th Workshop on Digital Fluid Power, DFP 2017
CountryDenmark
CityAalborg
Period07/09/201708/09/2017

Fingerprint

Model predictive control
Fluids
Controllers
Energy efficiency

Keywords

  • Fluid Power
  • Digital Displacement
  • Model Predictive Control

Cite this

Hansen, A. H., Asmussen, M. F., & Bech, M. M. (2017). Energy Optimal Tracking Control with Discrete Fluid Power Systems using Model Predictive Control. In Proceedings of 9th Workshop on Digital Fluid Power, DFP 2017 Department of Energy Technology, Aalborg University.
Hansen, Anders Hedegaard ; Asmussen, Magnus Færing ; Bech, Michael Møller. / Energy Optimal Tracking Control with Discrete Fluid Power Systems using Model Predictive Control. Proceedings of 9th Workshop on Digital Fluid Power, DFP 2017. Department of Energy Technology, Aalborg University, 2017.
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abstract = "For Discrete Displacement Cylinder (DDC) drives the control task lies in choosing force level. Hence, which force level to apply and thereby which pressure level each cylinder chambers shall be connected to. The DDC system is inherently a force system why often a force reference is generated by a tracking controller and translated into a discrete force level in a Force Shifting Algorithm (FSA). In the current paper the tracking controller and the FSA are combined in a Model Predictive Control algorithm solving the tracking problem while minimizing the energy use. Two MPC algorithms are investigated and compared to a PID like tracking controller combined with a FSA. The results indicate that the energy efficiency of position tracking DDC systems may be improved significantly by using the MPC algorithm.",
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Hansen, AH, Asmussen, MF & Bech, MM 2017, Energy Optimal Tracking Control with Discrete Fluid Power Systems using Model Predictive Control. in Proceedings of 9th Workshop on Digital Fluid Power, DFP 2017. Department of Energy Technology, Aalborg University, 9th Workshop on Digital Fluid Power, DFP 2017, Aalborg, Denmark, 07/09/2017.

Energy Optimal Tracking Control with Discrete Fluid Power Systems using Model Predictive Control. / Hansen, Anders Hedegaard; Asmussen, Magnus Færing; Bech, Michael Møller.

Proceedings of 9th Workshop on Digital Fluid Power, DFP 2017. Department of Energy Technology, Aalborg University, 2017.

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearch

TY - GEN

T1 - Energy Optimal Tracking Control with Discrete Fluid Power Systems using Model Predictive Control

AU - Hansen, Anders Hedegaard

AU - Asmussen, Magnus Færing

AU - Bech, Michael Møller

PY - 2017/9

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N2 - For Discrete Displacement Cylinder (DDC) drives the control task lies in choosing force level. Hence, which force level to apply and thereby which pressure level each cylinder chambers shall be connected to. The DDC system is inherently a force system why often a force reference is generated by a tracking controller and translated into a discrete force level in a Force Shifting Algorithm (FSA). In the current paper the tracking controller and the FSA are combined in a Model Predictive Control algorithm solving the tracking problem while minimizing the energy use. Two MPC algorithms are investigated and compared to a PID like tracking controller combined with a FSA. The results indicate that the energy efficiency of position tracking DDC systems may be improved significantly by using the MPC algorithm.

AB - For Discrete Displacement Cylinder (DDC) drives the control task lies in choosing force level. Hence, which force level to apply and thereby which pressure level each cylinder chambers shall be connected to. The DDC system is inherently a force system why often a force reference is generated by a tracking controller and translated into a discrete force level in a Force Shifting Algorithm (FSA). In the current paper the tracking controller and the FSA are combined in a Model Predictive Control algorithm solving the tracking problem while minimizing the energy use. Two MPC algorithms are investigated and compared to a PID like tracking controller combined with a FSA. The results indicate that the energy efficiency of position tracking DDC systems may be improved significantly by using the MPC algorithm.

KW - Fluid Power

KW - Digital Displacement

KW - Model Predictive Control

M3 - Article in proceeding

BT - Proceedings of 9th Workshop on Digital Fluid Power, DFP 2017

PB - Department of Energy Technology, Aalborg University

ER -

Hansen AH, Asmussen MF, Bech MM. Energy Optimal Tracking Control with Discrete Fluid Power Systems using Model Predictive Control. In Proceedings of 9th Workshop on Digital Fluid Power, DFP 2017. Department of Energy Technology, Aalborg University. 2017