In this paper, a comprehensive robustness analysis is given for a feedback linearization procedure applied to a Permanent Magnet Synchronous Motor. Linearizing feedback is designed with reference torque tracking objective. To address the issue of real-life applicability, simulations are performed in the presence of uncertain parameters, and external disturbances. Load characteristics, and uncertain system parameters are varied along with the amplitude of harmonics originating from the motor design. Parametric sensitivity and cross-effects are highlighted via random forest regression. Moreover, robustness against controller tuning is also tested via Monte Carlo-based tuning set generation. The cost function for the evaluation in both cases is assembled from linearizing quality and nominal performance. The results show a solid basis for later developments towards real-life application.

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Data-Driven Robustness Analysis for the Exact Linearization of Synchronous Motors

  • Dávid Somogyi,
  • Zoltán Téczely,
  • Bálint Kiss

摘要

In this paper, a comprehensive robustness analysis is given for a feedback linearization procedure applied to a Permanent Magnet Synchronous Motor. Linearizing feedback is designed with reference torque tracking objective. To address the issue of real-life applicability, simulations are performed in the presence of uncertain parameters, and external disturbances. Load characteristics, and uncertain system parameters are varied along with the amplitude of harmonics originating from the motor design. Parametric sensitivity and cross-effects are highlighted via random forest regression. Moreover, robustness against controller tuning is also tested via Monte Carlo-based tuning set generation. The cost function for the evaluation in both cases is assembled from linearizing quality and nominal performance. The results show a solid basis for later developments towards real-life application.