Journal
IEEE TRANSACTIONS ON POWER ELECTRONICS
Volume 38, Issue 3, Pages 3152-3162Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPEL.2022.3225626
Keywords
Predictive models; Bandwidth; Observers; Permanent magnet motors; Inductance; Robustness; Cost function; Extended state observer (ESO); model predictive control; permanent magnet synchronous motor (PMSM) drive; quadratic programming
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This article proposes a precise model-aided extended state observer (MAESO) compensation-based real-time model predictive current controller, which has enhanced parameter robustness performance and high bandwidth. The predictive controller is converted into the form of multiparameter quadratic programming for online solution using numerical computational method and the constraints are linearized. The disturbances estimated by MAESO are fed back to the controller in the form of parameters for cycle-by-cycle compensation without extra controller design. Comparative simulations and experiments under different operating conditions are carried out to verify the effectiveness and superiority of the proposed method.
Model predictive current controller is a popular and effective technique to provide fast dynamic response in the field of motor control. However, conventional predictive controllers are susceptible to deteriorating control performance when model mismatch exists, such as changes in motor parameters due to the temperature variations. Therefore, this article proposes a precise model-aid extended state observer (MAESO) compensation-based real-time model predictive current controller with enhanced parameter robustness performance and high bandwidth. The predictive controller is converted into the form of multiparameter quadratic programming for online solution using numerical computational method and the constraints are linearized. In addition, the disturbances estimated by MAESO are fed back to the controller in the form of parameters for cycle-by-cycle compensation without extra controller design. Comparative simulations and experiments under different operating conditions are carried out to verify the effectiveness and superiority of the proposed method.
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