Dynamic Threshold Adjustment-Based Event-Triggered Model Predictive Control for PMSM Motor

This paper proposes a dynamic threshold adjustment-based event-triggered strategy with finite control set model predictive control (FCS-MPC) for permanent magnet synchronous motor (PMSM). A critical innovation is the dynamic adjustment of the threshold inequality in the event-triggered technique. By incorporating the perturbation compensator to dynamically adjust the threshold, the event-triggering condition is unaffected by parameter drift and fast dynamic changes. In the absence of triggering, the control framework retains the control signal as constant. Upon fulfillment of the triggering condition, the FCS-MPC scheme is activated to generate an updated optimal control signal. To balance control performance and switching frequency, an adjustable coefficient is incorporated into the modified threshold inequality. The proposed method can flexibly reduce switching frequency while alleviating the computational burden by eliminating redundant operations. Extensive experimental studies validate the effectiveness of the proposed method.