• DocumentCode
    2104387
  • Title

    Direct torque control of induction machines based on predictive control

  • Author

    Liao Wei ; Su Mei

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Central South Univ., Changsha, China
  • fYear
    2010
  • fDate
    29-31 July 2010
  • Firstpage
    3295
  • Lastpage
    3300
  • Abstract
    To reduce the electromagnetic torque ripple of induction machines under conventional direct torque control, a improved direct torque control based on predictive algorithm is proposed. The control strategy predicts the change of electromagnetic torque and stator flux magnitude for each output voltage vector of inverter in several steps using a discrete-time model of an induction machine. An objective function consisted of predictions of electromagnetic torque, stator flux magnitude and its dynamic errors is proposed as an optimal control rule. The stability of the system was analyzed through the Pole-Zero map of closed-loop transfer function. Based on that, the optimal solution is obtained through minimizing the objective function. A simple algorithm to obtain the optimal solution is proposed for the voltage vector of inverter being finite. The new control strategy possess fast dynamic response and reduce the electromagnetic torque ripple effectively. Simulation study verify the feasibility of the proposed method.
  • Keywords
    asynchronous machines; closed loop systems; machine control; optimal control; poles and zeros; predictive control; stability; torque control; transfer functions; Pole-Zero map; closed-loop transfer function; direct torque control; discrete-time model; electromagnetic torque ripple; induction machines; optimal control rule; predictive control; stator flux magnitude; Electromagnetics; Induction machines; Inverters; Prediction algorithms; Predictive control; Torque; Torque control; Direct Torque Control; Predictive Control; Torque Ripple;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (CCC), 2010 29th Chinese
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-6263-6
  • Type

    conf

  • Filename
    5573304