永磁同步电机（Permanent Magnet Synchronous Motor, PMSM）具有效率高、功率因数大等优点而被广泛应用于航空航天、风力发电等领域。研究如何提高 PMSM 系统的控制性能对促进工业现代化生产的发展具有重要意义。然而，随着 PMSM 的广泛应用，其非线性、强耦合的缺点越来越明显，传统的控制方案难以解决电机控制性能不佳的问题。因此，本文为了使 PMSM 获得更好的控制性能，针对双闭环预测控制方案
展开研究。本文主要工作如下：

1. 针对 PMSM 控制系统在受到外界干扰时动态响应速度慢、抗干扰性能差的问题，对模型预测控制（Model Predictive Control, MPC）和无差拍预测控制（DeadbeatPredictive Control, DPC）相结合的双闭环预测控制方案展开了研究。首先对传统的矢量控制和 PI+DPC 的双闭环控制方案进行了简要分析；其次引出 MPC+DPC 的双闭环预测控制方案，并运用 MPC 和 DPC 算法分别设计了速度控制器和电流控制器；最后通
过仿真表明 MPC+DPC 的双闭环预测控制方案比前两种控制方案的控制性能更好。
2. 为了进一步提高 PMSM 控制系统速度和电流的动态响应性能和抗干扰性能且实现无超调，提出了基于灰色预测的双闭环预测控制方案以及基于灰色预测和降阶Luenberger 观测器的双闭环预测控制方案。首先在电流环引入了灰色预测模型；其次在速度环设计了基于降阶 Luenberger 观测器的速度控制器；最后通过仿真证明，本文所提出的两种控制方案的优越性，且后者的控制性能更好。
3. 为了进一步证明本文所提出的基于灰色预测的双闭环预测控制方案以及基于灰色预测和降阶 Luenberger 观测器的双闭环预测控制方案的有效性，搭建了 PMSM 控制系统实验平台。首先对系统的硬件和软件进行了分析；其次将本文提出的两种控制方案与 MPC+DPC 的双闭环预测控制方案进行实验对比；最后通过实验结果证明了本文提出的两种控制方案的动态响应性能和抗干扰性能都得到了提高。

本文对 PMSM 的双闭环预测控制方案展开了研究，通过在电流环引入灰色预测模型、在速度环设计降阶 Luenberger 观测器，提出了控制性能更加优越的两种控制方案，有利于提高 PMSM 在实际工业生产过程中的使用效率。

Permanentmagneticsynchronousmotor(PMSM)iswidelyappliedinfieldssuchasaerospace and wind power generation due to their high efficiency and large power factor. Studying how to improve the control performance of permanent magnet synchronous motor systems is of great significance in promoting the development of modern industrial production. However, due to the widespread application of permanent magnet synchronous motors, the drawbacks of their non-linearity and strong coupling have become more and more apparent, and the problem of differences in motor control performance cannot be solved by conventional control methods. Therefore,  in order to obtain better control performance of the permanent magnetic synchronous motor, the double closed loop prediction control method was examined in this paper. The main work of this paper is as follows:
1. The PMSM control system has a problem that the response speed is slow and the inter-ference resistance is poor when it receives interference from the outside. A double closed-loop
Predictive Control scheme combining Model Predictive Control (MPC) and Deadbeat Predictive Control (DPC) is studied. Firstly, we briefly analyzed the conventional vector control and
PI+DPC double closed loop control method. Secondly, the double closed-loop predictive control scheme of MPC+DPC is introduced, and the speed controller and the current controller are
designed respectively by using MPC algorithm and DPC algorithm. Finally, the simulation results show that the MPC+DPC double closed loop prediction control method has better control
performance than the previous two types of control methods.
2. In order to further improve the dynamic response performance and interference prevention performance of the PMSM control system, ensure that the system is free of overshoots, a
double closed loop predictive control scheme based on grey prediction and a double closed-loop predictive control scheme based on grey prediction and a reduced order Luenberger observer is proposed. Firstly, a grey prediction model is introduced in the current loop. Secondly, a velocity controller based on the reduced order Luenberger observer is designed in the velocity
loop. Finally, the simulation results show that the two control schemes proposed in this paperare superior, and the control performance of the latter is better.
3. In order to further prove the validity of the double closed-loop predictive control scheme based on grey prediction and the double closed-loop predictive control scheme based on grey
prediction and reduced order Luenberger observer proposed in this paper, an experimental platform of PMSM control system was established. Firstly, we analyzed the hardware and software
of the system. Secondly, the double closed-loop predictive control scheme based on grey prediction and the MPC+DPC double closed-loop predictive control scheme are experimented and
compared. Finally, the experimental results show that the dynamic response performance and anti-interference performance of the two control schemes proposed in this paper are improved.
In this paper,we investigated the double closed loop prediction control method for PMSM. By introducing the grey prediction model in the current loop, we designed a drop Luenberger
observer in the velocity loop and proposed two control proposals with better control performance. All of these help improve the use efficiency of PMSM in actual industrial production process.