Selective laser melting is a promising additive manufacturing technology enabling the fabrication of highly customizable products. A major challenge in selective laser melting is ensuring the quality of produced parts, which is influenced greatly by the thermal history of printed layers. We propose a Batch-Model Predictive Control technique based on the combination of model predictive control and iterative learning control. This approach succeeds in rejecting both repetitive and non-repetitive disturbances and thus achieves improved tracking performance and process quality. In a simulation study, the selective laser melting dynamics is approximated with a reduced-order control-oriented linear model to ensure reasonable computational complexity. The proposed approach provides convergence to the desired temperature field profile despite model uncertainty and disturbances.
@article{arxiv.2111.08363,
title = {Batch Model Predictive Control for Selective Laser Melting},
author = {Riccardo Zuliani and Efe C. Balta and Alisa Rupenyan and John Lygeros},
journal= {arXiv preprint arXiv:2111.08363},
year = {2022}
}