Application of Model Predictive Control in Discrete Displacement Cylinders to Drive a Knuckle Boom Crane

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Resumé

In this paper, two Discrete Displacement Cylinders (DDCs) are used to drive the boom of a knuckle boom crane. DDCs operate by connecting one of several available pressure levels to each chamber in order to produce different forces. A trade-off exists with such systems, between the accuracy of tracking and energy dissipation due to switching. A popular way to approach this problem is a Force Shifting Algorithm (FSA). However, in this paper, the trade-off is managed by use of a Model Predictive Control (MPC) algorithm. The tracking accuracy and energy efficiency of the MPC and FSA strategies for DDCs are compared to a PID strategy for standard cylinders. The comparison is obtained by use of a computer simulation of a knuckle boom crane performing a realistic load cycle. The load cycle consists of the crane extending to pick up a load and then retracting to place it at an appropriate location. The main results show that MPC can deliver smoother and more accurate motion than FSA, while using less energy. Compared with standard cylinders and PID control, MPC uses less energy, but due to the switching of chamber pressures, the motion is smoother with the standard strategy. Both FSA and MPC can have degraded performance when a large change in load is introduced.
OriginalsprogEngelsk
TitelProceedings of the 2018 Global Fluid Power Society PhD Symposium
Antal sider7
ForlagIEEE Press
Publikationsdato25 sep. 2018
Sider1-7
Artikelnummer8472363
ISBN (Trykt)978-1-5386-4786-8
ISBN (Elektronisk)978-1-5386-4785-1
DOI
StatusUdgivet - 25 sep. 2018
Begivenhed2018 Global Fluid Power Society PhD Symposium (GFPS) - Samara, Rusland
Varighed: 18 jul. 201820 jul. 2018

Konference

Konference2018 Global Fluid Power Society PhD Symposium (GFPS)
LandRusland
BySamara
Periode18/07/201820/07/2018

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Model predictive control
Cranes
Three term control systems
Energy efficiency
Energy dissipation
Computer simulation

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    Citer dette

    Donkov, V. H., Andersen, T. O., Pedersen, H. C., & Ebbesen, M. K. (2018). Application of Model Predictive Control in Discrete Displacement Cylinders to Drive a Knuckle Boom Crane. I Proceedings of the 2018 Global Fluid Power Society PhD Symposium (s. 1-7). [8472363] IEEE Press. https://doi.org/10.1109/GFPS.2018.8472363
    Donkov, Viktor Hristov ; Andersen, Torben Ole ; Pedersen, Henrik Clemmensen ; Ebbesen, Morten Kjeld. / Application of Model Predictive Control in Discrete Displacement Cylinders to Drive a Knuckle Boom Crane. Proceedings of the 2018 Global Fluid Power Society PhD Symposium . IEEE Press, 2018. s. 1-7
    @inproceedings{55c2046d73fb47ad91050d8aff663471,
    title = "Application of Model Predictive Control in Discrete Displacement Cylinders to Drive a Knuckle Boom Crane",
    abstract = "In this paper, two Discrete Displacement Cylinders (DDCs) are used to drive the boom of a knuckle boom crane. DDCs operate by connecting one of several available pressure levels to each chamber in order to produce different forces. A trade-off exists with such systems, between the accuracy of tracking and energy dissipation due to switching. A popular way to approach this problem is a Force Shifting Algorithm (FSA). However, in this paper, the trade-off is managed by use of a Model Predictive Control (MPC) algorithm. The tracking accuracy and energy efficiency of the MPC and FSA strategies for DDCs are compared to a PID strategy for standard cylinders. The comparison is obtained by use of a computer simulation of a knuckle boom crane performing a realistic load cycle. The load cycle consists of the crane extending to pick up a load and then retracting to place it at an appropriate location. The main results show that MPC can deliver smoother and more accurate motion than FSA, while using less energy. Compared with standard cylinders and PID control, MPC uses less energy, but due to the switching of chamber pressures, the motion is smoother with the standard strategy. Both FSA and MPC can have degraded performance when a large change in load is introduced.",
    keywords = "Discrete Displacement Cylinders, Knuckle Boom Crane, Model predictive control",
    author = "Donkov, {Viktor Hristov} and Andersen, {Torben Ole} and Pedersen, {Henrik Clemmensen} and Ebbesen, {Morten Kjeld}",
    year = "2018",
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    Donkov, VH, Andersen, TO, Pedersen, HC & Ebbesen, MK 2018, Application of Model Predictive Control in Discrete Displacement Cylinders to Drive a Knuckle Boom Crane. i Proceedings of the 2018 Global Fluid Power Society PhD Symposium ., 8472363, IEEE Press, s. 1-7, Samara, Rusland, 18/07/2018. https://doi.org/10.1109/GFPS.2018.8472363

    Application of Model Predictive Control in Discrete Displacement Cylinders to Drive a Knuckle Boom Crane. / Donkov, Viktor Hristov; Andersen, Torben Ole; Pedersen, Henrik Clemmensen; Ebbesen, Morten Kjeld.

    Proceedings of the 2018 Global Fluid Power Society PhD Symposium . IEEE Press, 2018. s. 1-7 8472363.

    Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

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    AU - Donkov, Viktor Hristov

    AU - Andersen, Torben Ole

    AU - Pedersen, Henrik Clemmensen

    AU - Ebbesen, Morten Kjeld

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    N2 - In this paper, two Discrete Displacement Cylinders (DDCs) are used to drive the boom of a knuckle boom crane. DDCs operate by connecting one of several available pressure levels to each chamber in order to produce different forces. A trade-off exists with such systems, between the accuracy of tracking and energy dissipation due to switching. A popular way to approach this problem is a Force Shifting Algorithm (FSA). However, in this paper, the trade-off is managed by use of a Model Predictive Control (MPC) algorithm. The tracking accuracy and energy efficiency of the MPC and FSA strategies for DDCs are compared to a PID strategy for standard cylinders. The comparison is obtained by use of a computer simulation of a knuckle boom crane performing a realistic load cycle. The load cycle consists of the crane extending to pick up a load and then retracting to place it at an appropriate location. The main results show that MPC can deliver smoother and more accurate motion than FSA, while using less energy. Compared with standard cylinders and PID control, MPC uses less energy, but due to the switching of chamber pressures, the motion is smoother with the standard strategy. Both FSA and MPC can have degraded performance when a large change in load is introduced.

    AB - In this paper, two Discrete Displacement Cylinders (DDCs) are used to drive the boom of a knuckle boom crane. DDCs operate by connecting one of several available pressure levels to each chamber in order to produce different forces. A trade-off exists with such systems, between the accuracy of tracking and energy dissipation due to switching. A popular way to approach this problem is a Force Shifting Algorithm (FSA). However, in this paper, the trade-off is managed by use of a Model Predictive Control (MPC) algorithm. The tracking accuracy and energy efficiency of the MPC and FSA strategies for DDCs are compared to a PID strategy for standard cylinders. The comparison is obtained by use of a computer simulation of a knuckle boom crane performing a realistic load cycle. The load cycle consists of the crane extending to pick up a load and then retracting to place it at an appropriate location. The main results show that MPC can deliver smoother and more accurate motion than FSA, while using less energy. Compared with standard cylinders and PID control, MPC uses less energy, but due to the switching of chamber pressures, the motion is smoother with the standard strategy. Both FSA and MPC can have degraded performance when a large change in load is introduced.

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