Kalman Filter–Based Disturbance Observer Assisted Model Predictive Control for Dual Three-Phase PMSM Drives

Abstract

The dual three-phase permanent magnet synchronous machine (DTP-PMSM) is considered a promising candidate for applications requiring high power density and improved reliability. Continuous control set model predictive control (CCS-MPC) has been widely employed for DTP-PMSM drives to minimize harmonic subspace currents while satisfying the electromagnetic torque demand. However, due to model mismatches, inverter nonlinearities, and harmonics in the back electromotive force (EMF), conventional MPC schemes are prone to steady-state errors and increased current harmonics. To address these issues, this article proposes a robust CCS-MPC strategy incorporating a Kalman filter–based disturbance observer (DOB) to estimate and compensate for unmodeled disturbances within the prediction model. The proposed method improves current tracking performance and suppresses harmonic distortions in both the fundamental and harmonic subspaces. The effectiveness of the proposed control strategy is validated through simulations in the MATLAB/Simulink environment under machine parameter variations. The results demonstrate improved robustness and reduced steady-state errors and current harmonics compared with conventional MPC approaches.