The parameter mismatch problem has a great impact on the control performance of model predictive control, which is however unavoidable during the operation. In order to improve the system robustness against the parameter mismatches and disturbances, an improved direct model predictive current control with a disturbance observer is proposed in this article, where the disturbance observer is realized by an incremental moving horizon estimator. Moreover, another concern raised from the applications of direct model predictive current control is the computational burden, especially for the long-horizon implementations. Therefore, a dual reference frame solution for the surface permanent-magnet synchronous motor (SPMSM) is proposed in this article to allocate a great proportion of heavy computations required for the optimization problem to the offline preparation, which can reduce the computational burden by almost 50% on average for a prediction horizon of five time-steps. Besides, the parameter mismatch effects of individual electrical parameters on the control performance of the model predictive direct current control method are investigated and quantified via simulations. A five-step direct model predictive current control is implemented on a dSPACE system with a sampling frequency of 20 kHz to validate the effectiveness of the proposed scheme with an SPMSM drive system.     «

The parameter mismatch problem has a great impact on the control performance of model predictive control, which is however unavoidable during the operation. In order to improve the system robustness against the parameter mismatches and disturbances, an improved direct model predictive current control with a disturbance observer is proposed in this article, where the disturbance observer is realized by an incremental moving horizon estimator. Moreover, another concern raised from the applications...     »