Data-Driven Adaptive Control for Laser-Based Additive Manufacturing with Automatic Controller Tuning

被引:24
作者
Chen, Lequn [1 ,2 ]
Yao, Xiling [1 ]
Chew, Youxiang [1 ]
Weng, Fei [1 ]
Moon, Seung Ki [2 ]
Bi, Guijun [1 ]
机构
[1] Agcy Sci Technol & Res, Singapore Inst Mfg Technol, 73 Nanyang Dr, Singapore 637662, Singapore
[2] Nanyang Technol Univ, Sch Mech & Aerosp Engn, 50 Nanyang Ave, Singapore 639798, Singapore
来源
APPLIED SCIENCES-BASEL | 2020年 / 10卷 / 22期
关键词
additive manufacturing; direct energy deposition; closed-loop control; virtual reference feedback tuning; FABRICATION; DESIGN; VRFT;
D O I
10.3390/app10227967
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Closed-loop control is desirable in direct energy deposition (DED) to stabilize the process and improve the fabrication quality. Most existing DED controllers require system identifications by experiments to obtain plant models or layer-dependent adaptive control rules, and such processes are cumbersome and time-consuming. This paper proposes a novel data-driven adaptive control strategy to adjust laser voltage with the melt pool size feedback. A multitasking controller architecture is developed to incorporate an autotuning unit that optimizes controller parameters based on the DED process data automatically. Experimental validations show improvements in the geometric accuracy and melt pool consistency of controlled samples. The main advantage of the proposed controller is that it can adapt to DED processes with different part shapes, materials, tool paths, and process parameters without tweaking. System identification is not required even when process conditions are changed, which reduces the controller implementation time and cost for end-users.
引用
收藏
页码:1 / 19
页数:18
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