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A Modified Iterative Learning Control Approach for the Active Suppression of Rotor Vibration Induced by Coupled Unbalance and Misalignment

  • Yifan Bao,
  • Jianfei Yao,
  • Fabrizio Scarpa,
  • Yan Li

摘要

This paper proposes a modified iterative learning control (MILC) periodical feedback-feedforward algorithm to reduce the vibration of a rotor caused by coupled unbalance and parallel misalignment. The control of the vibration of the rotor is provided by an active magnetic actuator (AMA). The iterative gain of the MILC algorithm here presented has a self-adjustment based on the magnitude of the vibration. Notch filters are adopted to extract the synchronous (1 × Ω) and twice rotational frequency (2 × Ω) components of the rotor vibration. Both the notch frequency of the filter and the size of feedforward storage used during the experiment have a real-time adaptation to the rotational speed. The method proposed in this work can provide effective suppression of the vibration of the rotor in case of sudden changes or fluctuations of the rotor speed. Simulations and experiments using the MILC algorithm proposed here are carried out and give evidence to the feasibility and robustness of the technique proposed.