• DocumentCode
    133452
  • Title

    ITAE-optimal PI controller based on Genetic Algorithm for low-order process with large time delays

  • Author

    Pan Fengping ; Liao Hongkai ; Luo Jia ; Xue Yali

  • Author_Institution
    Electr. Power Res. Inst. of Guangdong Power Group Co., Guangzhou, China
  • fYear
    2014
  • fDate
    12-13 Sept. 2014
  • Firstpage
    134
  • Lastpage
    139
  • Abstract
    For low order process with large time delay, a kind of optimal PI controller tuning method is proposed based on generalized Hermite-Biehler theorem and Genetic Algorithm. Firstly, the calculation method of parameter stable region of PI controller that can stabilize a low order process with time delay is proposed by using the generalized Hermite-Biehler theorem. Then the optimum PI controller parameters are obtained within this region based on ITAE criterion and genetic algorithm. A PI controller tuning formula is finally obtained by nonlinear fitting of optimization results, which has the capability to cover the low order process with normalized time delays up to 100. Monte-Carlo stochastic experiment on robust performance indicates that the proposed PI controller tuning method has good performance robustness when parameter uncertainty occurs compared with other four PI tuning methods.
  • Keywords
    PI control; delays; genetic algorithms; optimal control; ITAE criterion; ITAE optimal PI controller tuning method; Monte Carlo stochastic experiment; PI controller tuning formula; generalized Hermite-Biehler theorem; genetic algorithm; large time delays; low order process; normalized time delays; optimization; optimum PI controller; robustness; Delay effects; Genetic algorithms; Indexes; Process control; Robustness; Tuning; Uncertainty; Genetic Algorithm; Hermite-Biehler Theorem; ITAE index; Monte-Carlo stochastic experiment; Optimal PI control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation and Computing (ICAC), 2014 20th International Conference on
  • Conference_Location
    Cranfield
  • Type

    conf

  • DOI
    10.1109/IConAC.2014.6935475
  • Filename
    6935475