永磁伺服电机复合模型预测控制

永磁电机效率和功率密度高、力矩和惯量比大，是工业伺服领域的主流电机。伺服控制技术是充分发挥永磁电机优势、提升伺服系统运行性能的关键。目前，永磁伺服系统多采用多环级联的比例 积分（PI）控制器，但由于积分器的滞后效应，PI动态响应速度较慢，抗干扰能力较差，难以满足机械臂、精密加工等高性能伺服控制的动、静态性能要求。因此，提出一种广义模型预测控制与有限集模型预测控制相结合的复合模型预测控制策略。此外，还提出一种广义模型预测控制的低运算量实现方法及一种机械参数估计方法。试验结果表明，所提复合模型预测控制可提高永磁伺服电机的动态响应速度和抗负载扰动能力。

Composite Model Predictive Control for Permanent Magnet Servo Motor

Permanent magnet motor is the mainstream motor in the industrial servo field for its high efficiency, high power density, and large torque and inertia ratio. Servo control technology is the key to give full play to the advantages of permanent magnet motor and improve the performance of servo system. At present, permanent magnet servo system mostly adopts multi loop cascaded proportional integral (PI) controllers. However, due to the lag effect of the integrator, the dynamic response speed of PI is slow and the anti interference ability is poor, which is difficult to meet the dynamic and static performance requirements of high performance servo control such as mechanical arm and precise machining. Therefore, a composite model predictive control strategy combining generalized model predict control and finite control set model perdict control is proposed. In addition, a low computational complexity implementation method of generalized model predictive control and a mechanical parameter estimation method are also proposed. The experimental results show that the proposed composite model predictive control can improve the dynamic response speed and load disturbance rejection capability of the permanent magnet servo motor.