• DocumentCode
    2136536
  • Title

    Adaptive Unified Predictive Control applied to first-order-plus-dead-time processes to eliminate unknown class of deterministic disturbance

  • Author

    Lin, Shu-Kai ; Lee, An-Chen

  • Author_Institution
    Dept. of Mech. Eng., Nat. Chiao-Tung Univ., Hsinchu, Taiwan
  • fYear
    2011
  • fDate
    11-15 April 2011
  • Firstpage
    149
  • Lastpage
    156
  • Abstract
    A novel Adaptive Unified Predictive Control method (Adaptive-UPC) is proposed and applied to the first-order-plus-dead-time (FOPDT) process models with model uncertainties under unknown deterministic disturbances. Based on Indirect Self-tuning Regulator, this new control structure is constructed by combining UPC controller, Recursive Least-Squares Estimation with forgetting factor (RLS with forgetting factor) and Variable Regression Estimation (VRE). The simulation results show that the method can be effectively applied to first-order-plus-dead-time (FOPDT) process models with uncertain process parameters (gain, time constant and dead-time) and unknown deterministic disturbance.
  • Keywords
    adaptive control; least squares approximations; predictive control; recursive estimation; regression analysis; self-adjusting systems; uncertain systems; adaptive unified predictive control method; deterministic disturbance elimination; first-order-plus-dead-time process model; indirect self-tuning regulator; recursive least-squares estimation; variable regression estimation; First order plus dead time process; Model uncertainty; RLS with forgetting factor; Unified predictive control; Unknown disturbance; VRE;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence in Control and Automation (CICA), 2011 IEEE Symposium on
  • Conference_Location
    Paris
  • Print_ISBN
    978-1-4244-9902-1
  • Type

    conf

  • DOI
    10.1109/CICA.2011.5945741
  • Filename
    5945741