Untitled Document




> Archives > To Be Published 


Recently
Accepted Papers 
Double Vector Based Model Predictive Torque Control for SPMSM Drives with Improved SteadyState Performance
XiaoGuang Zhang, YiKang He, and BenShuai Hou 
Abstract 
In order to further improve the steadystate control performance of model predictive torque control (MPTC), a doublevectorbased model predictive torque control without a weighting factor is proposed in this paper. The extended voltage vectors synthesized by two basic voltage vectors are used to increase the number of feasible voltage vectors. Therefore, the control precision of the torque and the stator flux along with the steadystate performance can be improved. To avoid testing all of the feasible voltage vectors, the solution of deadbeat torque control is calculated to predict the reference voltage vector. Thus, the candidate voltage vectors, which need to be evaluated by a cost function, can be reduced based on the sector position of the predicted reference voltage vector. Furthermore, a cost function, which only includes a reference voltage tracking error, is designed to eliminate the weighting factor. Moreover, two voltage vectors are applied during one control period, and their durations are calculated based on the principle of reference voltage tracking error minimization. Finally, the proposed method is tested by simulations and experiments. 
Keyword 
Model predictive torque control, Surface mounted permanentmagnet synchronous motor (SPMSM), Weighting factor 
PDF 




