Research On Double Closed-loop Predictive Control For Permanent Magnet Synchronous Motor

Permanent magnetic synchronous motor(PMSM)is widely applied in fields such as aerosp?ace 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.There fore,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 Predic-tive 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 con-trol 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 re-sults 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 preven-tion 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 paper are 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 plat-form 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 pre-diction 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 perfor-mance.All of these help improve the use efficiency of PMSM in actual industrial production process.