Model predictive control of layer width in wire arc additive manufacturing

Abstract

Abstract Wire arc additive manufacturing (WAAM) is an emerging technology in the manufacturing industry, which uses a welding arc as an energy source to fuse metal wire and deposit layer by layer. In order to promote its manufacture precision, stability, and repeatability, it’s crucial to develop a feedback control strategy for WAAM. This research implements vision-based feedback control for the layer width during the WAAM process. A WAAM system is developed using a robot and CMT welder with a visual sensing system. The dynamics of the layer width in WAAM process is modeled experimentally. An ARX dynamic model is built. Based on this model, a model predictive control (MPC) strategy is derived to regulate the WAAM process. Feedback control experiments were conducted to verify the tracking and robustness performance of the proposed MPC algorithm.