High Performance Model Predictive Control for PMSM by Using Stator Current Mathematical Model Self-Regulation Technique

Fengxiang Wang, Kunkun Zuo, Peng Tao, Jose Rodriguez

Resultado de la investigación: Contribución a una revistaArtículorevisión exhaustiva

2 Citas (Scopus)

Resumen

Excellent control performance and high robustness under different operating conditions are primary purposes pursued by many model predictive control algorithms. As a model-based control algorithm, the accuracy of the stator current mathematical model has a significant impact on the control performance of the predictive current control (PCC) method. To improve the current tracking accuracy and the robustness against parameter variation, a stator current mathematical model self-regulation strategy, which uses stator current prediction error to calculate parameter changes and design a parameter variation compensation strategy to correct the mathematical model in real-time at each control cycle, based on PCC algorithm is proposed to pursue desired performance. Consequently, the elimination of stator current prediction error, high controlled quality, and better robustness have been achieved in the proposed method. The comparative simulation and experiment results validate the superiority of the proposed method.

Idioma originalInglés
Número de artículo9094347
Páginas (desde-hasta)13652-13662
Número de páginas11
PublicaciónIEEE Transactions on Power Electronics
Volumen35
N.º12
DOI
EstadoPublicada - dic 2020

Áreas temáticas de ASJC Scopus

  • Ingeniería eléctrica y electrónica

Huella

Profundice en los temas de investigación de 'High Performance Model Predictive Control for PMSM by Using Stator Current Mathematical Model Self-Regulation Technique'. En conjunto forman una huella única.

Citar esto