通过基于卡尔曼滤波的超局部模型补偿感应电机无模型预测控制中的测量误差

In model predictive control, ensuring the accuracy and robustness of the prediction model is crucial. A Kalman filter (KF) is a self-correction method commonly used as an observer for state estimation in uncertain applications. Model-free predictive control utilizes an ultra-local model for prediction purposes. Precise measurements and feedback gains are required for accuracy. This study proposes ...