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Robust Predictive Control for Linear Permanent Magnet Synchronous Motor Drives Based on an Augmented Internal Model Disturbance Observer

To optimize the current-control performance of the linear permanent magnet synchronous motor (LPMSM) drive system, a robust continuous time model-based predictive control for the LPMSM drive systems is proposed in this article. Since the current regulation technology is fundamental for obtaining the precise thrust of the LPMSM, a continuous time model-based predictive control is utilized in the current loop to achieve a fast dynamic response and accurate tracking accuracy. However, the predictive control is a model-based scheme, thus, the model uncertainties and parameter variations will influence the accuracy of stator current. To solve this problem, an augmented internal model disturbance observer is proposed to estimate the lumped disturbances and then compensate to the forward channel. First, the internal model equation of the current loop is constructed by the internal model control principle. Then, a new augmented matrix is constructed by introducing the error variables of the actual current and the internal model current. The observer control law is designed by the state feedback theory, and the observer parameters are optimized by pole assignment method. Finally, the experimental results demonstrate the correctness and effectiveness of the proposed method.