• DocumentCode
    2471446
  • Title

    Layer-to-layer height control of Laser Metal Deposition processes

  • Author

    Tang, Lie ; Ruan, Jianzhong ; Sparks, Todd E. ; Landers, Robert G. ; Liou, Frank

  • Author_Institution
    Dept. of Mech. & Aerosp. Eng., Missouri Univ. of Sci. & Technol., Rolla, MO, USA
  • fYear
    2009
  • fDate
    10-12 June 2009
  • Firstpage
    5582
  • Lastpage
    5587
  • Abstract
    A laser metal deposition (LMD) height controller design methodology is presented in this paper. The height controller utilizes the particle swarm optimization (PSO) algorithm to estimate model parameters between layers using measured temperature and track height profiles. The process model parameters for the next layer are then predicted using exponentially weighted moving average (EWMA). Using the predicted model, the powder flow rate reference profile, which will produce the desired layer height reference, is then generated using Iterative Learning Control (ILC). The model parameter estimation capability is tested using a four-layer deposition. The results demonstrate the simulation based upon estimated process parameters matches the experimental results quite well. The experimental deposition using this methodology demonstrates good tracking of the height reference in terms of the finished track.
  • Keywords
    adaptive control; iterative methods; laser deposition; learning systems; moving average processes; particle swarm optimisation; process control; spatial variables control; exponentially weighted moving average; iterative learning control; laser metal deposition processes; layer-to-layer height control; model parameter estimation; particle swarm optimization; Design methodology; Laser modes; Optical control; Parameter estimation; Particle measurements; Particle swarm optimization; Particle tracking; Predictive models; Temperature control; Temperature measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference, 2009. ACC '09.
  • Conference_Location
    St. Louis, MO
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4244-4523-3
  • Electronic_ISBN
    0743-1619
  • Type

    conf

  • DOI
    10.1109/ACC.2009.5160407
  • Filename
    5160407