1. Model predictive control of layer width in wire arc additive manufacturing
- Author
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Huijun Li, Shanben Chen, Chunyang Xia, Joseph Polden, Yanling Xu, Shiyu Zhang, Zengxi Stephen Pan, and Long Wang
- Subjects
0209 industrial biotechnology ,Materials science ,Strategy and Management ,Feedback control ,02 engineering and technology ,Welding ,Management Science and Operations Research ,021001 nanoscience & nanotechnology ,Industrial and Manufacturing Engineering ,law.invention ,Model predictive control ,020901 industrial engineering & automation ,law ,Control theory ,Robustness (computer science) ,Robot ,0210 nano-technology ,Energy source ,Sensing system - 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.
- Published
- 2020
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