Model Predictive Control Strategies in Switched Reluctance Motor Drives—An Overview
Jun Cai, Xiaolan Dou, Adrian David Cheok, Wen Ding, Ying Yan, Xin Zhang
Abstract
Model predictive control (MPC) is an advanced control technique with salient features, such as simplicity applied in multivariable systems, fast-transient response, inclusion of nonlinearities, and straightforward constraints in the control law, which is attracted in applying for high-performance control of motor drives. The electromagnetic characteristics of the switched reluctance motor (SRM) are of highly nonlinearity, which may result in lower control accuracy, slow stabilization time of control variables, unsatisfactory dynamic response, and torque ripples elimination performance. This article presents an overview of the current finite control set and continuous control set based MPC strategies in SRM drives. The model predictive current control, torque control, and flux control are analyzed from perspectives of modeling schemes, switching vectors optimization approaches, cost function selections, and the control performance. And finally, the current challenges and future development trends in applying the MPC technologies in SRM drives are also discussed.