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The performance of electrical machineshighly depends on the control properties (dynamics, accuracy,robustness, switching states selection, and optimization). Good dynamics of the response must be followed byhigh accuracy of the references tracking and minimization of the switching losses. Those are problematic issues in caseof linear controllers, when their limitations are considered. Model Predictive Control (MPC) is considered as one alternative toclassical controllers for electric machines.MPCis a conceptually different control technique that offers a high flexibility to control different electrical machinesand to manage several control objectives, without adding significant complexity to the system. MPC has demonstrated to be easier to implement and understand than classical speed control techniques such as FOC and DTC providing a control of AC machines. MPC can dramatically change the way electrical energy is controlled using power semiconductors, and it offers challenging opportunities for research in electrical drives.

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Topics of interest include, but are not limited to:

  • Sensorless MPC for electrical machines

  • Direct model-based torque-speedcontrol

  • Application tomega-watt range wind turbines

  • Cost function design and weighting factors tuning

  • Fixed switching frequency

  • Robustness against parameter change

  • Fault tolerant MPC

  • MPC for multiphase drives

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重要日期
  • 会议日期

    10月29日

    2017

    11月01日

    2017

  • 11月01日 2017

    注册截止日期

主办单位
IEEE工业电子学会
承办单位
东南大学
中国科学院自动化研究所
中国科学院数学与系统科学学院
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