Model-free adaptive iterative learning control of melt pool width in wire arc additive manufacturing
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ORIGINAL ARTICLE
Model-free adaptive iterative learning control of melt pool width in wire arc additive manufacturing Chunyang Xia 1,2
&
Zengxi Pan 1 & Shiyu Zhang 1 & Huijun Li 1 & Yanling Xu 2 & Shanben Chen 2
Received: 4 June 2020 / Accepted: 24 August 2020 # Springer-Verlag London Ltd., part of Springer Nature 2020
Abstract Wire arc additive manufacturing (WAAM) is a Direct Energy Deposition (DED) technology, which utilize electrical arc as heat source to deposit metal material bead by bead to make up the final component. However, issues like the lack of assurance in accuracy, repeatability and stability hinder the further application in industry. Therefore, a Model Free Adaptive Iterative Learning Control (MFAILC) algorithm was developed to be applied in WAAM process in this study. The dynamic process of WAAM is modelled by adaptive neuro fuzzy inference system (ANFIS). Based on this ANFIS model, simulations are performed to demonstrate the effectiveness of MFAILC algorithm. Furthermore, experiments are conducted to investigate the tracking performance and robustness of the MFAILC controller. This work will help to improve the forming accuracy and automatic level of WAAM. Keywords Model free adaptive . Iterative learning control . Additive manufacturing . ANFIS . WAAM
1 Introduction Over the past decades, additive manufacturing (AM) technology has been developed continuously due to its advantages in design flexibility and time efficiency. Considered as a game changing technology [1], AM technology has been applied in many fields, such as aerospace [2], automotive [3], biomedical [4, 5] and architectural design. Nowadays, AM techniques has been extended to rapid repair and rapid tooling from original direct fabrication [6]. As a result, AM industry grows rapidly and its value estimated to be over $30 billion by 2022 [7]. Wire arc additive manufacturing (WAAM) is a new emerging AM technology, which makes use of an electric arc as heat-source to deposit metal material layer-by-layer, which makes up the final part (as illustrated in Fig. 1). It is one of fast-growing direct forming technology in AM field in recent
* Zengxi Pan [email protected] 1
School of Mechanical, Materials, Mechatronic and Biomedical Engineering, University of Wollongong, Northfields Ave, Wollongong, NSW 2522, Australia
2
School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
years. Compared with other AM method, it possesses the features of higher deposition efficiency, lower equipment cost, higher material utilization rate, and clear production environment [8]. However, as pointed out in related literatures [9, 10], precision and repeatability during AM process hind its further development. To overcome those challenges, in situ monitoring and control have received increasing attention, which were considered as an effective way to improve the final quality of production. According to a road map workshop on measurement science needs for metal-based AM [11], process monitoring and feedback
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