Research On Model Predictive Control Optimization Of Permanent Magnet Synchronous Motor

Permanent magnet synchronous motor(PMSM)is widely used in industry,agriculture,national defense and transportation.PMSM has many advantages such as high power factor,simple structure,low noise and energy saving.In order to achieve high-precision and low-complexity control,most PMSM control systems use an online optimization model predictive control(MPC)method.However,due to the large amount of calculation and sensitivity to parameter change and external disturbance,the traditional MPC method results in poor real-time performance and anti-disturbance performance.This paper has carried on the optimization research of model predictive control method.The main work of this paper is as follows:(1)The basic structure and mathematical model of PMSM are analyzed.Based on the theory of rotating coordinate system,the conversion relationship of mathematical model in abc,αβ and dq axis coordinate system is derived.The basic working mechanism of model predictive control is studied,and the advantages and disadvantages of model predictive torque control and current control are analyzed.(2)Research on the model direct torque control(MPDTC)of vector set optimization.The traditional MPDTC method needs to traverse all voltage vectors,resulting in a large amount of calculation and poor real-time performance.In order to solve this problem,a vector control set optimized MPDTC algorithm is proposed.The optimization algorithm estimates the expected voltage vector based on the idea of deadbeat,selects the candidate voltage vector in the sector based on the position of the desired voltage vector.So that it can reduce the candidate voltage vector,and optimizes the calculation amount of the algorithm.The model and simulation experiments are carried out under Matlab / Simulink environment.Compared with the traditional torque prediction scheme,The results show that the optimization algorithm reduces the amount of calculation while maintaining the superior dynamic and steady-state performance of the traditional algorithm.(3)Research on Model Predictive Current Control(MPCC)based on disturbance compensation.The traditional MPCC method is sensitive to parameters and disturbances.It is prone to overshoot and oscillation.In order to overcome this problem,a current prediction control strategy based on disturbance compensation is proposed in this paper.Based on the mathematical model and simulation experiment analysis,the controller parameter value deviation is verified against permanent magnet The effect of synchronous motor current prediction control performance.Based on the idea of disturbance compensation,the optimization algorithm designed a extended state observer(ESO)to observe disturbance.Then introduce the disturbanceinto prediction equation to construct a prediction model with disturbance compensation.In Matlab/Simulink environment,the anti-disturbance performance of the optimized algorithm is verified.Compared with the anti-disturbance performance of traditional current prediction methods,which proves that the optimized algorithm has better anti-disturbance performance.