Speed‐Current Dual‐Loop Model Predictive Control for LIM

This study addresses the inherent limitations of conventional PI control in speed regulation systems, particularly its poor robustness. A dual‐loop model predictive control (MPC) strategy integrating speed and current loops is proposed, treating the motor as a multi‐input multi‐output system to effectively mitigate issues such as weak robustness and slow dynamic response during operation. The speed loop employs Model Predictive Speed Control (MPSC) for speed regulation. However, since MPC performance partially relies on the accuracy of the motor's mathematical model, load disturbances may degrade control performance. To address this, a load observer is introduced for the LIM speed loop to estimate and compensate for disturbances, significantly improving control accuracy. Meanwhile, the current loop employs model predictive flux control (MPFC), enhanced by an improved generalized dual‐vector control strategy to optimize steady‐state performance, thereby effectively reducing current ripple and torque pulsation. Simulation results demonstrate that the proposed dual‐loop MPC strategy exhibits superior performance under speed step changes and load disturbances, featuring minimal overshoot, fast dynamic response, high steady‐state accuracy, and strong anti‐interference capability. Additionally, the observer effectively tracks the given load. This study provides a practical control solution for high‐performance LIM applications in rail transit and industrial automation.