TR2020-122

Stable Adaptive Estimation for Speed-sensorless Induction Motor Drives: A Geometric Approach


    •  Wang, Y., Satake, A., Furutani, S., Sano, S., "Stable Adaptive Estimation for Speed-sensorless Induction Motor Drives: A Geometric Approach", International Conference on Electrical Machines (ICEM), August 2020.
      BibTeX TR2020-122 PDF
      • @inproceedings{Wang2020aug,
      • author = {Wang, Yebin and Satake, Akira and Furutani, Shinichi and Sano, Sota},
      • title = {Stable Adaptive Estimation for Speed-sensorless Induction Motor Drives: A Geometric Approach},
      • booktitle = {International Conference on Electrical Machines (ICEM)},
      • year = 2020,
      • month = aug,
      • url = {https://www.merl.com/publications/TR2020-122}
      • }
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  • Research Areas:

    Control, Signal Processing

Rotor speed estimation is one of the key problems in speed-sensorless motor drives. Adaptation-based approaches, assuming the rotor speed as a parameter and based on the original coordinates, admit simple estimator designs, albeit suffer from the lack of guaranteed convergence of estimation error dynamics. Focusing on stable speed estimation, this paper proposes a new algorithm based on transforming the motor model into an adaptive observer form via a change of state coordinates. The resultant adaptive estimator renders globally exponentially convergent estimation error dynamics, under persistent excitation condition. The proposed algorithm is advantageous for its guaranteed stability, ease of tuning, and robustness. Experiments demonstrate its effectiveness.