估计员
控制理论(社会学)
电流(流体)
模型预测控制
永磁同步电动机
地平线
磁铁
计算机科学
控制(管理)
物理
工程类
数学
人工智能
电气工程
统计
天文
作者
Zichao Gao,Yuxing Zhang,Deng Chen,Xiaohu Xie
标识
DOI:10.1109/epee63731.2024.10875417
摘要
The variation of motor parameters during motor operation has a significant impact on model predictive control (MPC), a model-based control strategy. In order to reduce the effects of parameter mismatch and external disturbances on motor control, this paper proposes a robust model predictive current control method with moving horizon estimator (MHE). The method utilizes MHE to form a disturbance observer, consolidating the effects of parameter mismatch and other unknown disturbances into a single estimation term. The estimated disturbance is then fed into the model predictive current controller for current prediction and optimal voltage calculation. Meanwhile, an incremental model of the motor is adopted in the model predictive current controller, to eliminate the effect of the rotor magnetic flux. The simulation results indicate that the proposed method practically eliminates the steady-state error caused by parameter mismatch and effectively enhances the robustness of current control.
科研通智能强力驱动
Strongly Powered by AbleSci AI