Reduced-order multivariable modeling and nonlinear control of melt-pool geometry and temperature in directed energy deposition

Qian Wang, Jianyi Li, Michael Gouge, Abdalla Ramadan Nassar, Pan Michaleris, Edward William Reutzel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

There has been continuing effort in developing analytical, numerical and empirical models of laser-based additive manufacturing (AM) processes in the literature. However, advanced physics-based models that can be directly used for feedback control design, i.e., control-oriented models, are severely lacking. In this paper, we develop a reduced-order (in contrast to finite element models) multivariable model for directed energy deposition. One important difference between our model from the existing work lies in a novel parameterization of the material transfer rate in the deposition as a function of the process operating parameter. Such parameterization allows a more accurate characterization of the steady-state melt-pool geometry compared to the existing lumped-parameter analytical models. Predictions of melt-pool geometry and temperature from our model are validated using experimental data obtained from deposition of Ti-6AL-4V on a laser engineering net shaping (LENS) AM process and finite element analysis. Then based on this reduced-order multivariable model, we design a nonlinear multi-input multi-output (MIMO) control, specifically a feedback linearization control, to track both melt-pool height and temperature reference trajectories using laser power and laser scan speed.

Original languageEnglish (US)
Title of host publication2016 American Control Conference, ACC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages845-851
Number of pages7
ISBN (Electronic)9781467386821
DOIs
StatePublished - Jul 28 2016
Event2016 American Control Conference, ACC 2016 - Boston, United States
Duration: Jul 6 2016Jul 8 2016

Publication series

NameProceedings of the American Control Conference
Volume2016-July
ISSN (Print)0743-1619

Other

Other2016 American Control Conference, ACC 2016
CountryUnited States
CityBoston
Period7/6/167/8/16

Fingerprint

Geometry
3D printers
Temperature
Lasers
Parameterization
Feedback linearization
Feedback control
Analytical models
Physics
Trajectories
Finite element method

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

Wang, Q., Li, J., Gouge, M., Nassar, A. R., Michaleris, P., & Reutzel, E. W. (2016). Reduced-order multivariable modeling and nonlinear control of melt-pool geometry and temperature in directed energy deposition. In 2016 American Control Conference, ACC 2016 (pp. 845-851). [7525019] (Proceedings of the American Control Conference; Vol. 2016-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACC.2016.7525019
Wang, Qian ; Li, Jianyi ; Gouge, Michael ; Nassar, Abdalla Ramadan ; Michaleris, Pan ; Reutzel, Edward William. / Reduced-order multivariable modeling and nonlinear control of melt-pool geometry and temperature in directed energy deposition. 2016 American Control Conference, ACC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 845-851 (Proceedings of the American Control Conference).
@inproceedings{d03ae583adf5405e81e92d6e932133e0,
title = "Reduced-order multivariable modeling and nonlinear control of melt-pool geometry and temperature in directed energy deposition",
abstract = "There has been continuing effort in developing analytical, numerical and empirical models of laser-based additive manufacturing (AM) processes in the literature. However, advanced physics-based models that can be directly used for feedback control design, i.e., control-oriented models, are severely lacking. In this paper, we develop a reduced-order (in contrast to finite element models) multivariable model for directed energy deposition. One important difference between our model from the existing work lies in a novel parameterization of the material transfer rate in the deposition as a function of the process operating parameter. Such parameterization allows a more accurate characterization of the steady-state melt-pool geometry compared to the existing lumped-parameter analytical models. Predictions of melt-pool geometry and temperature from our model are validated using experimental data obtained from deposition of Ti-6AL-4V on a laser engineering net shaping (LENS) AM process and finite element analysis. Then based on this reduced-order multivariable model, we design a nonlinear multi-input multi-output (MIMO) control, specifically a feedback linearization control, to track both melt-pool height and temperature reference trajectories using laser power and laser scan speed.",
author = "Qian Wang and Jianyi Li and Michael Gouge and Nassar, {Abdalla Ramadan} and Pan Michaleris and Reutzel, {Edward William}",
year = "2016",
month = "7",
day = "28",
doi = "10.1109/ACC.2016.7525019",
language = "English (US)",
series = "Proceedings of the American Control Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "845--851",
booktitle = "2016 American Control Conference, ACC 2016",
address = "United States",

}

Wang, Q, Li, J, Gouge, M, Nassar, AR, Michaleris, P & Reutzel, EW 2016, Reduced-order multivariable modeling and nonlinear control of melt-pool geometry and temperature in directed energy deposition. in 2016 American Control Conference, ACC 2016., 7525019, Proceedings of the American Control Conference, vol. 2016-July, Institute of Electrical and Electronics Engineers Inc., pp. 845-851, 2016 American Control Conference, ACC 2016, Boston, United States, 7/6/16. https://doi.org/10.1109/ACC.2016.7525019

Reduced-order multivariable modeling and nonlinear control of melt-pool geometry and temperature in directed energy deposition. / Wang, Qian; Li, Jianyi; Gouge, Michael; Nassar, Abdalla Ramadan; Michaleris, Pan; Reutzel, Edward William.

2016 American Control Conference, ACC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 845-851 7525019 (Proceedings of the American Control Conference; Vol. 2016-July).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Reduced-order multivariable modeling and nonlinear control of melt-pool geometry and temperature in directed energy deposition

AU - Wang, Qian

AU - Li, Jianyi

AU - Gouge, Michael

AU - Nassar, Abdalla Ramadan

AU - Michaleris, Pan

AU - Reutzel, Edward William

PY - 2016/7/28

Y1 - 2016/7/28

N2 - There has been continuing effort in developing analytical, numerical and empirical models of laser-based additive manufacturing (AM) processes in the literature. However, advanced physics-based models that can be directly used for feedback control design, i.e., control-oriented models, are severely lacking. In this paper, we develop a reduced-order (in contrast to finite element models) multivariable model for directed energy deposition. One important difference between our model from the existing work lies in a novel parameterization of the material transfer rate in the deposition as a function of the process operating parameter. Such parameterization allows a more accurate characterization of the steady-state melt-pool geometry compared to the existing lumped-parameter analytical models. Predictions of melt-pool geometry and temperature from our model are validated using experimental data obtained from deposition of Ti-6AL-4V on a laser engineering net shaping (LENS) AM process and finite element analysis. Then based on this reduced-order multivariable model, we design a nonlinear multi-input multi-output (MIMO) control, specifically a feedback linearization control, to track both melt-pool height and temperature reference trajectories using laser power and laser scan speed.

AB - There has been continuing effort in developing analytical, numerical and empirical models of laser-based additive manufacturing (AM) processes in the literature. However, advanced physics-based models that can be directly used for feedback control design, i.e., control-oriented models, are severely lacking. In this paper, we develop a reduced-order (in contrast to finite element models) multivariable model for directed energy deposition. One important difference between our model from the existing work lies in a novel parameterization of the material transfer rate in the deposition as a function of the process operating parameter. Such parameterization allows a more accurate characterization of the steady-state melt-pool geometry compared to the existing lumped-parameter analytical models. Predictions of melt-pool geometry and temperature from our model are validated using experimental data obtained from deposition of Ti-6AL-4V on a laser engineering net shaping (LENS) AM process and finite element analysis. Then based on this reduced-order multivariable model, we design a nonlinear multi-input multi-output (MIMO) control, specifically a feedback linearization control, to track both melt-pool height and temperature reference trajectories using laser power and laser scan speed.

UR - http://www.scopus.com/inward/record.url?scp=84992156921&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84992156921&partnerID=8YFLogxK

U2 - 10.1109/ACC.2016.7525019

DO - 10.1109/ACC.2016.7525019

M3 - Conference contribution

T3 - Proceedings of the American Control Conference

SP - 845

EP - 851

BT - 2016 American Control Conference, ACC 2016

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Wang Q, Li J, Gouge M, Nassar AR, Michaleris P, Reutzel EW. Reduced-order multivariable modeling and nonlinear control of melt-pool geometry and temperature in directed energy deposition. In 2016 American Control Conference, ACC 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 845-851. 7525019. (Proceedings of the American Control Conference). https://doi.org/10.1109/ACC.2016.7525019