Model predictive control of laser metal deposition

  • Yangbo LiuEmail author
  • Liuping Wang
  • Milan Brandt


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.


Laser metal deposition Product quality control Model predictive control Melt pool size 



Laser metal deposition


Laser additive manufacturing


Near-infrared monochrome


Model predictive controller


Recursive least squares


Proportional integral and derivative


Generalised predictive control


Complementary metal oxide semiconductor


Field of view


Frames per second


The relationship between the laser power and the melt pool size


Computer numerical control


Low power model


High power model


Frequency average model


Industry standard architecture



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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.Wuhan National Laboratory for OptoelectronicsWuhanPeople’s Republic of China
  2. 2.School of EngineeringRMITMelbourneAustralia

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