A non-linear adaptive backstepping controller based on linear extend state observer (NABESO) is designed to track speed of PMSM. This study proposes a two-channel strategy which is applied for the online elimination of the influence of unknown load torque and parameters disturbances. According to the strategy, an adaptive controller is designed to eliminate the load torque and parameters disturbance of the first channel, and a linear extended state observer is chosen in a feedforward method to observe the internal time-varying parameters disturbance of the second channel as well as compensating the disturbances from the first channel. The proposed strategy can not only achieve online estimation of the load disturbance, but also suppress disturbances caused by the changes of all parameters, and to some extent, the negative transient response can also be avoided by abandoning traditional cascade control mode. Besides the functional advantages, the proposed controller is of pertinence and flexibility in parameters selection. Finally, the simulation and experimental results both display that the proposed strategy can effectively suppress the impact of internal and external disturbance on the PMSM control performance.
In order to improve the dynamic response performance and robustness of the permanent magnet synchronous motor control system and optimize the parameter adjustment of the control system, a motor control method based on single‐loop model prediction and moment of inertia parameter identification with forgetting factor is proposed. First, the motor state equation in the prediction model is designed, and the single‐loop model predictive control method is proposed. Then, comparing the effects of various parameters of the motor on the running stability of the motor, a least‐squares identification method based on forgetting factor is added to identify the moment of inertia online and optimize the prediction model in real time. The simulation and experimental results show that the proposed method has good dynamic performance for the permanent magnet synchronous motor adapting to the rotational speed and load variation. At the same time, the addition of the moment of inertia identification enhances the accuracy and system robustness of the motor model parameters during the model prediction process. This method provides an effective way of engineering control. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
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