An improved FCS-MPC strategy for PMSM based on grey prediction and fuzzy dynamic weighting factors

To optimize the performance and minimize transition times of control systems for permanent magnet synchronous motors (PMSM), this study suggests a double closed-loop FCS-MPC approach. Utilizing grey prediction and fuzzy dynamic weighting factors, the strategy is designed for PMSM applications. Initially, the mathematical model of PMSM is implemented in the two-phase synchronous rotation coordinate system to introduce the double closed-loop FCS-MPC method. This includes the use of distinct model predictive controllers for the speed outer loop and current inner loop. Subsequently, the grey system is integrated into the current inner loop to precisely determine the q-axis reference current for an optimal voltage vector, enhancing resistance to interference and dynamic response capabilities. Furthermore, a fuzzy controller is incorporated to minimize transition times by dynamically adjusting weighting factors based on varying operational conditions. This strategy aims to prevent speed overshooting, reduce transition times, and enhance resistance to interference and dynamic response. The efficacy of the proposed approach is verified through simulation and experimental assessments. DOI: 10.61416/ceai.v26i4.9103