Optimized-Sector-Based Model Predictive Torque Control With Sliding Mode Controller for Switched Reluctance Motor
Xiaodong Sun, Yiliang Zhu, Yingfeng Cai, Ming Yao, Yueping Sun, Gang Lei
Abstract
In this article, an optimized-sector-based model predictive torque control (OSB-MPTC) strategy is proposed to reduce the torque ripple of the switched reluctance motors (SRMs). First, a phase torque estimation method based on the magnetic coenergy and Fourier series expansion is introduced. A new sector division rule and a selection of the basic voltage vector in predicting torque are then introduced. The cost function for minimizing torque error is designed to select the optimal voltage vector. In addition, a new reaching law is proposed to improve the robustness of the control system and the dynamic response of the speed loop. Finally, experiments are carried out on a 12/8 pole three-phase SRM prototype to verify the performance of the proposed control method in detail. Compared with the conventional model predictive control, the proposed OSB-MPTC with global robust sliding mode control has better performance in terms of suppression of the torque ripple, speed dynamic response, and robustness.