Model-free adaptive iterative learning control of melt pool width in wire arc additive manufacturing

© 2020, Springer-Verlag London Ltd., part of Springer Nature. 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

Intelligentized technologies for welding manufacturing

This paper presents some newest and potential developments on artificial intelligent technologies for welding manufacturing process in Shanghai Jiao Tong University (SJTU), which contains multi-information acquirement and fusion processing of arc welding dynamical process; Intelligent computing for welding process; Intelligent control methods for welding process and quality control; artificial intelligent technologies for welding robot systems and robotic welding process; and some application in welding engineering. The ideas of intelligentized welding manufacturing technology (IWMT) and intelligentized welding manufacturing engineering (IWME) are presented in this paper for systematization of intending researches and applications on intelligentized technologies for modern welding manufacturing