• DocumentCode
    2756302
  • Title

    A Novel Robust Tuning Strategy for Model Predictive Control

  • Author

    Han, Kai ; Zhao, Jun ; Qian, Jixin

  • Author_Institution
    Inst. of Syst. Eng., Zhejiang Univ., Hangzhou
  • Volume
    2
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    6406
  • Lastpage
    6410
  • Abstract
    A novel and easy-to-use robust tuning strategy for model predictive control (MPC) is presented. The proposed strategy based on min-max algorithm can deal with model uncertainty explicitly; it could design an MPC controller with strong robustness and small overshooting, owing to the performance index employed in the strategy. Another contribution of the performance index is to avoid large prediction horizon and control horizon being selected to MPC controllers, which can reduce the MPC online computation. The superiority of the proposed robust tuning strategy has been demonstrated by simulation results
  • Keywords
    minimax techniques; performance index; predictive control; robust control; uncertain systems; control horizon; min-max algorithm; model predictive control; model uncertainty; online computation; performance index; prediction horizon; robust tuning; Algorithm design and analysis; Industrial control; Modeling; Performance analysis; Predictive control; Predictive models; Robust control; Robustness; Systems engineering and theory; Uncertainty; MPC; Min-Max optimization; PSO; autotuning; performance index;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
  • Conference_Location
    Dalian
  • Print_ISBN
    1-4244-0332-4
  • Type

    conf

  • DOI
    10.1109/WCICA.2006.1714318
  • Filename
    1714318