A Quadratic-Optimal Repetitive Process Controller for Laser Metal Deposition
Abstract
Methods of process control are needed in order to advance additive manufacturing technology towards widespread commercial use. Here an optimal repetitive process controller (RPC) is developed for controlling part height in laser metal deposition (LMD), an additive manufacturing process in which metal powder is blown into a melt pool and parts are built in a layer-by-layer fashion. As with many additive processes, the geometry of the printed part depends not only on process parameters (laser power, table velocity, etc.), but also on the dynamics of the material addition process itself. The process is modeled with 2D dynamics, combining inlayer dynamics and layer-to-layer dynamics. The in-layer dynamics describe how material is distributed within the melt pool while the layer-to-layer dynamics describe how the heights of previous layers propagate through the part. This modeling framework allows for the design of an RPC. An optimal RPC is designed by using a lifted-system representation of the 2D dynamics and solving a quadratic cost function. The controller is implemented in experiment and the control performance is observed for different weighting parameters.
Recommended Citation
M. L. Gegel et al., "A Quadratic-Optimal Repetitive Process Controller for Laser Metal Deposition," Proceedings of the 2018 Annual American Control Conference (2018, Milwaukee, WI), pp. 4446 - 4451, Institute of Electrical and Electronics Engineers (IEEE), Jun 2018.
The definitive version is available at https://doi.org/10.23919/ACC.2018.8431847
Meeting Name
2018 Annual American Control Conference, ACC (2018: Jun. 27-29, Milwaukee, WI)
Department(s)
Mechanical and Aerospace Engineering
Research Center/Lab(s)
Intelligent Systems Center
International Standard Book Number (ISBN)
978-1-5386-5428-6
International Standard Serial Number (ISSN)
0743-1619
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2018 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jun 2018
Comments
This work was supported by the Chancellor's Distinguished Fellowship at Missouri University of Science and Technology, the National Science Foundation (CMMI1301414), the Center for Aerospace Manufacturing Technology and Optomec Inc.