• DocumentCode
    3091872
  • Title

    Stochastic adaptive predictive temperature control for PET blow molding machines

  • Author

    Chang, Ya-Ling ; Tsai, Ching-Chih

  • Author_Institution
    Dept. of Electr. Eng., Nat. Chung-Hsing Univ., Taichung, Taiwan
  • fYear
    2010
  • fDate
    15-17 June 2010
  • Firstpage
    143
  • Lastpage
    148
  • Abstract
    This paper presents a stochastic adaptive model reference predictive control (SMRPC) approach to achieving accurate temperature control for a polyethylene-terephthalate (PET) blow molding machine, which is experimentally modeled as a simple second-order system model with given long time delay. Based on this model, the adaptive model reference predictive controller with control weighting is derived based on the minimization of an expected generalized predictive control (GPC) performance criteria. A real-time adaptive SMRPC algorithm is proposed. Computer simulations show that the proposed control method is capable of giving accurate and satisfactory control performance under set-point changes and exogenous disturbances.
  • Keywords
    blow moulding; minimisation; model reference adaptive control systems; predictive control; stochastic processes; temperature control; PET blow molding machines; exogenous disturbances; generalized predictive control; minimization; polyethylene terephthalate; second order system model; set point changes; stochastic adaptive model reference predictive control; temperature control; Adaptive control; Delay effects; Positron emission tomography; Predictive control; Predictive models; Programmable control; Stochastic processes; Stochastic systems; Temperature control; Weight control; PET blow molding machine; adaptive control; generalized predictive control (GPC); model reference adaptive control; predictive control; temperature control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications (ICIEA), 2010 the 5th IEEE Conference on
  • Conference_Location
    Taichung
  • Print_ISBN
    978-1-4244-5045-9
  • Electronic_ISBN
    978-1-4244-5046-6
  • Type

    conf

  • DOI
    10.1109/ICIEA.2010.5515045
  • Filename
    5515045