Model predictive control of laser metal deposition

Abstract

Laser metal deposition (LMD) is one of the efficient processes in laser additive manufacturing (LAM) systems that uses metallic materials to produce metallic components additively. One of the remaining challenges for this type of systems is its product quality control. This paper proposes automatic control of melt pool size during the process of laser metal deposition. Using a low-cost near-infrared monochrome (NIRM) camera, the melt pool size is measured from grey melt pool image and is modelled by a first-order transfer function with time delay where the laser power is chosen to be the manipulated variable. Experimental data are used to identify the first-order plus delay model, which is then converted to a non-minimal state space realisation that accurately captures the time delay in discrete time with all state variables being measurable. A model predictive controller (MPC) is designed and implemented for controlling the melt pool size with the state space model. Experimental results are conducted on the platform TruLaser Cell 7020 from Trumpf, showing that the melt pool size has been successfully controlled to their desired specifications and the product quality measured by the variations of the brick height has been significantly improved.