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Abstract

Improving the geometric accuracy of the deposited component is essential for the wider adoption of wire arc additive manufacturing (WAAM) in industries. This paper introduces an online layer-by-layer controller that operates robustly under various welding conditions to improve the deposition accuracy of the WAAM process. Two control strategies are proposed and evaluated in this work: A PID algorithm and a multi-input multi-output model-predictive control (MPC) algorithm. After each layer of deposition, the deposited geometry is measured using a laser scanner. These measurements are compared against the CAD model, and geometric errors are then compensated by the controller, which generates a new set of welding parameters for the next layer. The MPC algorithm, combined with a linear autoregressive (ARX) modelling process, updates welding parameters between successive layers by minimizing a cost function based on sequences of input variables and predicted responses. Weighting coefficients of the ARX model are trained iteratively throughout the manufacturing process. The performance of the designed control architecture is investigated through both simulation and experiments. Results show that the real-time control performance is improved by increasing the complexity of implemented control algorithm: controlled geometric fluctuations in the test component were reduced by 200% whilst maintaining fluctuations within a 3 mm limit under various welding conditions. In addition, the adaptiveness of designed control strategy is verified by accurately controlling the fabrication of a part with complex geometry.

Details

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Title
Layer-by-layer model-based adaptive control for wire arc additive manufacturing of thin-wall structures
Author
Mu Haochen 1 ; Polden, Joseph 1 ; Li, Yuxing 1 ; He Fengyang 1 ; Xia Chunyang 1 ; Pan Zengxi 1   VIAFID ORCID Logo 

 University of Wollongong, School of Mechanical, Materials, Mechatronic and Biomedical Engineering, Wollongong, Australia (GRID:grid.1007.6) (ISNI:0000 0004 0486 528X) 
Publication title
Volume
33
Issue
4
Pages
1165-1180
Publication year
2022
Publication date
Apr 2022
Publisher
Springer Nature B.V.
Place of publication
London
Country of publication
Netherlands
ISSN
09565515
e-ISSN
15728145
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2022-03-10
Milestone dates
2022-01-31 (Registration); 2021-08-14 (Received); 2022-01-29 (Accepted)
Publication history
 
 
   First posting date
10 Mar 2022
ProQuest document ID
2639126759
Document URL
https://www.proquest.com/scholarly-journals/layer-model-based-adaptive-control-wire-arc/docview/2639126759/se-2?accountid=208611
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-01-10
Database
ProQuest One Academic