Sensitivity Analysis of Finite Control Set Model Predictive Direct Speed Control of PMSM

Finite control set model predictive control (FCS-MPC) stands out as a highly promising and extensively researched control approach due to its exceptional dynamic performance and the versatility it offers for defining control goals. This paper presents a systematic analysis of parameter mismatch and its impact on the control performance of finite control set model predictive direct speed control (FCS-MPDSC) for permanent magnet synchronous motor (PMSM). Variations in resistance, inductances, and inertia are studied, and root mean square error (RMSE) metrics are employed to quantify the effects of parameter mismatch on the phase current and angular speed. Results analyze the control performance and provide insights into addressing parameter mismatch challenges in FCS-MPDSC. The predictive control algorithm is designed in dq coordinate system and a linear Kalman filter (LKF) is utilized for the estimation of load torque.