Model Predictive Current Control Strategy Based on Dual Boundary Restriction of Segmented Long Stator Permanent Magnet Linear Synchronous Motor

Based on the consideration of reducing the switching loss of high-power converters, it is necessary to reduce the switching frequency of inverters on medium-speed maglev train. The finite set model predictive control (FCS-MPC) does not need modulation so that the PWM output delay can be eliminated under the low switching frequency. In this paper, an FCS-MPC strategy based on dual boundary restriction is applied to the medium-speed maglev system. When the stator current error exceeds the outer boundary circle, the optimal voltage vector is determined through the cost function directly. When the stator current error is between the inner and outer boundary circles, using the intersection of its quadratic form and the boundary restriction value to select the voltage vector. When the stator current error is inside the inner boundary circle, the switching state of inverters will not be changed. The experiment results showed that the proposed control strategy can realize the high performance of double closed-loop changeover control of the medium-speed maglev, and reduce the switching frequency of inverters effectively without increasing the traction output significantly.