基于事件触发的永磁同步电机多步模型预测转矩控制

针对多步模型预测控制(MPC)计算量大的问题，将事件触发机制引入到永磁同步电机(PMSM)多步模型预测转矩控制(MPTC)，建立基于转矩误差、磁链误差和连续触发次数的事件触发机制。当满足事件触发条件时，相应的采样周期无需多步预测计算，可从已有的控制序列中选择对应的电压矢量。仿真结果表明，基于事件触发的PMSM MPTC可行，由于事件触发时，牺牲滚动优化的特性，转矩和磁链脉动轻微增大，开关频率和平均运算量有所降低。

Multi-Step Model Prediction Torque Control of Permanent Magnet Synchronous Motor Based on Event Triggering

Multi-step model prediction control (MPC) of permanent magnet synchronous motor (PMSM) has a large computation. In order to solve the problemthe event trigger mechanism is introduced into PMSM multi-step model predictive torque control (MPTC). The event trigger mechanism is based on torque errorstator flux error and times of continuous event triggering. If the event is triggeredthe MPTC uses the voltage vector of control sequence in the most recent multi-step prediction directly to calculate the sampling period and does not carry out the multi-step prediction. Simulation results show that the PMSM MPTC based on event trigger can work properly. Compared with conventional MPTCthe torque and stator flux ripples of PMSM MPTC increase mildly as rolling optimization is sacrificed when the event is triggeredbut average switching frequency and computational burden decrease.