Distributed model predictive control for Ink-Jet 3D printing

Yijie Guo; Joost Peters; Tom Oomen; Sandipan Mishra

doi:10.1109/AIM.2017.8014056

Distributed model predictive control for Ink-Jet 3D printing

Yijie Guo
, Joost Peters
, Tom Oomen
, Sandipan Mishra

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

18 Citations (Scopus)

Abstract

This paper develops a closed-loop approach for ink-jet 3D printing. The control design is based on a distributed model predictive control scheme, which can handle constraints (such as droplet volume) as well as the large-scale nature of the problem. The high resolution of ink-jet 3D printing make centralized methods extremely time-consuming, thus a distributed implementation of the controller is developed. First a graph-based height evolution model that can capture the liquid flow dynamics is proposed. Then, a scalable closedloop control algorithm is designed based on the model using Distributed MPC, that reduces computation time significantly. The performance and efficiency of the algorithm are shown to outperform open-loop printing and closed-loop printing with existing Centralized MPC methods through simulation results.

Original language	English
Title of host publication	2017 IEEE International Conference on Advanced Intelligent Mechatronics, AIM 2017
Place of Publication	Piscataway
Publisher	Institute of Electrical and Electronics Engineers
Pages	436-441
Number of pages	6
ISBN (Electronic)	9781509059980
DOIs	https://doi.org/10.1109/AIM.2017.8014056
Publication status	Published - 21 Aug 2017
Event	2017 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, (AIM 2017) - Munich, Germany Duration: 3 Jul 2017 → 7 Jul 2017

Conference

Conference	2017 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, (AIM 2017)
Country/Territory	Germany
City	Munich
Period	3/07/17 → 7/07/17

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10.1109/AIM.2017.8014056

Cite this

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title = "Distributed model predictive control for Ink-Jet 3D printing",

abstract = "This paper develops a closed-loop approach for ink-jet 3D printing. The control design is based on a distributed model predictive control scheme, which can handle constraints (such as droplet volume) as well as the large-scale nature of the problem. The high resolution of ink-jet 3D printing make centralized methods extremely time-consuming, thus a distributed implementation of the controller is developed. First a graph-based height evolution model that can capture the liquid flow dynamics is proposed. Then, a scalable closedloop control algorithm is designed based on the model using Distributed MPC, that reduces computation time significantly. The performance and efficiency of the algorithm are shown to outperform open-loop printing and closed-loop printing with existing Centralized MPC methods through simulation results.",

author = "Yijie Guo and Joost Peters and Tom Oomen and Sandipan Mishra",

year = "2017",

month = aug,

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doi = "10.1109/AIM.2017.8014056",

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booktitle = "2017 IEEE International Conference on Advanced Intelligent Mechatronics, AIM 2017",

publisher = "Institute of Electrical and Electronics Engineers",

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note = "2017 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, (AIM 2017) ; Conference date: 03-07-2017 Through 07-07-2017",

}

Guo, Y, Peters, J, Oomen, T & Mishra, S 2017, Distributed model predictive control for Ink-Jet 3D printing. in 2017 IEEE International Conference on Advanced Intelligent Mechatronics, AIM 2017., 8014056, Institute of Electrical and Electronics Engineers, Piscataway, pp. 436-441, 2017 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, (AIM 2017), Munich, Germany, 3/07/17. https://doi.org/10.1109/AIM.2017.8014056

Distributed model predictive control for Ink-Jet 3D printing. / Guo, Yijie; Peters, Joost; Oomen, Tom et al.
2017 IEEE International Conference on Advanced Intelligent Mechatronics, AIM 2017. Piscataway: Institute of Electrical and Electronics Engineers, 2017. p. 436-441 8014056.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

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N2 - This paper develops a closed-loop approach for ink-jet 3D printing. The control design is based on a distributed model predictive control scheme, which can handle constraints (such as droplet volume) as well as the large-scale nature of the problem. The high resolution of ink-jet 3D printing make centralized methods extremely time-consuming, thus a distributed implementation of the controller is developed. First a graph-based height evolution model that can capture the liquid flow dynamics is proposed. Then, a scalable closedloop control algorithm is designed based on the model using Distributed MPC, that reduces computation time significantly. The performance and efficiency of the algorithm are shown to outperform open-loop printing and closed-loop printing with existing Centralized MPC methods through simulation results.

AB - This paper develops a closed-loop approach for ink-jet 3D printing. The control design is based on a distributed model predictive control scheme, which can handle constraints (such as droplet volume) as well as the large-scale nature of the problem. The high resolution of ink-jet 3D printing make centralized methods extremely time-consuming, thus a distributed implementation of the controller is developed. First a graph-based height evolution model that can capture the liquid flow dynamics is proposed. Then, a scalable closedloop control algorithm is designed based on the model using Distributed MPC, that reduces computation time significantly. The performance and efficiency of the algorithm are shown to outperform open-loop printing and closed-loop printing with existing Centralized MPC methods through simulation results.

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BT - 2017 IEEE International Conference on Advanced Intelligent Mechatronics, AIM 2017

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Y2 - 3 July 2017 through 7 July 2017

ER -

Distributed model predictive control for Ink-Jet 3D printing

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