Enhanced Model-Free Predictive Speed Control Without Weighting Factors for PMSM Based on Newly Designed Cost Function
Meizhou Yang, Xuan Wu, Sheng Huang, Wu Liao, Ting Wu, Yizhe Wang, Shoudao Huang
Abstract
The performance of finite control set model predictive speed control (FCS-MPSC) for permanent magnet synchronous motor (PMSM) suffers from parameter uncertainties. Model-free predictive speed control (MFPSC) has been proposed in the latest literature to improve robustness. However, its overall performance improvement is restricted due to the great difference between the electrical and mechanical time constant, and tedious weighting factors tuning. To address the problems, this paper proposes an enhanced MFPSC without weighting factors. First, in order to implicitly unify different time scales and improve the system’s dynamic performance, the ultra-local speed and current models are established through a reduced-order motor model. Then, the future state is predicted needing no accurate motor models based on the established ultra-local model. In this way, the robustness of the system is significantly strengthened. Moreover, a new cost function containing the speed and current information is designed based on the homogeneity of control variables principle. It avoids the weighting factors tuning and achieves the synchronous optimization of speed and current. To further improve the steady performance, a duty cycle calculation is presented according to the established cost function. Finally, the comparison results confirm the superiority of the proposed method.