Resistance based iterative learning control of additive manufacturing with wire
Artikel i vetenskaplig tidskrift, 2015
This paper presents successful feed forward control of additive manufacturing of fully dense metallic components. The study is a refinement of former control solutions of the process, providing more robust and industrially acceptable measurement techniques. The system uses a solid state laser that melts metal wire, which in turn is deposited and solidified to build the desired solid feature on a substrate. The process is inherently subjected to disturbances that might hinder consecutive layers to be deposited appropriately. The control action is a modified wire feed rate depending on the surface of the deposited former layer, in this case measured as a resistance. The resistance of the wire stick-out and the weld pool has shown to give an accurate measure of the process stability, and a solution is proposed on how to measure it. By controlling the wire feed rate based on the resistance measure, the next layer surface can be made more even. A second order iterative learning control algorithm is used for determining the wire feed rate, and the solution is implemented and validated in an industrial setting for building a single bead wall in titanium alloy. A comparison is made between a controlled and an uncontrolled situation when a relevant disturbance is introduced throughout all layers. The controller proves to successfully mitigate these disturbances and maintain stable deposition while the uncontrolled deposition fails.
Iterative learning control