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102 / 2025-02-22 19:25:04
A Sensorless Model Predictive Control for Induction Motor Based on Ultra-local Model
Model predictive control (MPC),sensorless control,sliding mode observer,ultra-local model
Review group 4
Final Paper
Yanqing Zhang / Xi'an University of Technology
Yuchen Wang / Xi'an University of Technology
Zhonggang Yin / Xi'an University of Technology
Yanping Zhang / Xi'an University of Technology
Cong Bai / Xi'an University of Technology
Baojia Ma / Xi'an University of Technology
In this paper, a sensorless model predictive control for induction motor using ultra-local model is studied. Firstly, the speed, stator flux, and stator resistance are estimated online using a sliding mode observer (SMO). Secondly, in sensorless model predictive control, due to the sensitivity of traditional predictive models to changes in motor parameters and the existence of errors between estimated and actual speeds, the accuracy of the predictive model will be reduced. In response to the above issues, this paper optimizes the prediction model. For the flux linkage prediction model, a correction term is introduced and the stator resistance in the flux linkage prediction model is updated in real-time through a sliding mode observer. For the current prediction model, an Ultra-local model is introduced instead of the traditional current prediction model, which does not consider any motor parameters. Therefore, this method has better robustness performance. Finally, the method was validated through simulation.
Important Date

  • Conference Date

    Jun 05

    2025

    to

    Jun 01

    2026

  • May 30 2025

    Draft paper submission deadline

  • Jun 08 2025

    Registration deadline

Sponsored By
China Southeast University
IEEE Power Electronics Society
Jiangsu Association of Automation
Nanjing Section IE Chapter
Organized By
Southeast University
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