异步电机无速度传感器模型预测控制

Model Predictive Control for Speed Sensorless Induction Motor Drive

模型预测控制(model predictive control,MPC)是近年来在交流电机控制领域得到广泛关注的一种优化控制方法。对于两电平逆变器驱动的异步电机系统,传统MPC需要对定子磁链和定子电流进行7次预测得到使目标函数最小的最佳电压矢量,计算量较大,不利于在线实施。通过解析推导定子电流和定子磁链之间的关系,该文提出一种改进的MPC,只需对定子磁链进行预测,省却了计算相对复杂的定子电流预测,使算法复杂性和计算量得到显著降低。另外在MPC的基础上,为了提高系统的可靠性和降低硬件成本,采用速度自适应全阶观测器实现了无速度传感器运行。文中考虑了数字控制延迟对MPC的影响,并提出了补偿方法,采用预励磁的方法获得较大的启动转矩并减小启动电流。最后在两电平逆变器异步电机平台上进行仿真和实验,结果表明,该文提出的无速度传感器模型预测控制,在较宽的速度范围内都具有良好的动静态性能。

As a kind of optimal control method, Model predictive control （MPC） attracts much attention in the area of AC motor drives recently. For two-level inverter-fed induction motor （IM） drives, conventional MPC needs to predict both stator flux and stator current for seven times to obtain the best voltage vector minimizing the cost function, which leads to high computational burden and is unfavorable for real-time implementation. Based on the analytical study of the relationship between stator flux and stator current, this paper proposed an improved MPC, which only needs to predict the stator flux and avoids the complicated stator current prediction. Hence, the control complexity and computational burden are significantly reduced. Furthermore, to improve the system reliability and reduce the hardware cost, speed adaptive full order observer was introduced to achieve sensorless operation. The influence of control delay was compensated and the strategy of pre-excitation was implemented to avoid large starting current while obtaining high starting torque. Finally, simulation and experimental studies were carried out on a two-level inverter-fed IM drive. The results prove that the proposed sensorless MPC can achieve excellent dynamic and steady state performance over a wide speed range.