MIMO Model Predictive Control of Bead Geometry in Wire Arc Additive Manufacturing

Publication Name

2021 IEEE 11th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2021


Geometric properties of material deposited by the wire arc additive manufacturing (WAAM) process often deviates from desired setpoints. To improve the accuracy and repeatability of the WAAM process, an effective control strategy to maintain desired deposition geometry that operates robustly under various welding conditions is required. In this work, a control strategy utilizing multi-input multi-output (MIMO) model-predictive control (MPC) is presented. This approach, based on linear autoregressive (ARX) modelling, aims to improve the accuracy and flexibility of deposited bead geometry in the WAAM process. The MPC controller updates welding parameters between successive layers by minimizing a cost function based on sequences of input variables. Measurements of deposited bead geometry are made by laser scanner and input to the linear ARX model, which then makes future bead geometry predictions. Weighting coefficients of the ARX model are trained iteratively throughout the manufacturing process. Experimental results show that the derived control strategy can reduce fluctuations in a part's height by 400% and maintain the fluctuation within an acceptable range. In addition, the fluctuations in bead width along a single weld seam was also improved by more than 50%.

Open Access Status

This publication is not available as open access

First Page


Last Page




Link to publisher version (DOI)