| Model Predictive Control(MPC)is a kind of process control.Compared with PID control,MPC has better dynamic performance and variable constraint ability.Applying MPC to the permanent magnet synchronous motor(PMSM)control system is of great significance for optimizing the structure of the PMSM control system and improving the dynamic performance of the PMSM.However,the delay of the calculation result caused by the excessive calculation of MPC in the control process seriously affects the actual control performance of PMSM.At the same time,the accuracy of the model parameters restricts the control precision and stability of MPC.In response to the above problems,this paper studies the following aspects of MPC:Firstly,according to the mathematical model of three-phase permanent magnet synchronous motor and the principle of MPC,the prediction model of MPC in synchronous rotating coordinate system is derived,and the prediction model is discretized by Euler discrete method,which is convenient for model predictive control.The preparation of the program.By analyzing the PMSM vector control strategy and the voltage space pulse width modulation strategy,combined with the model predictive control principle,the model predictive vector control structure is established,which lays a foundation for the later study of the PMSM model predictive controller and the optimal control structure.Secondly,the double closed-loop cascade structure of PMSM model predictive vector control is analyzed,and the design method of speed controller and current controller based on model prediction is given respectively.Due to the establishment of two MPC-based controllers,the computational complexity of the PMSM vector control system is multiplied.Aiming at the calculation problem of multiple MPC controllers,redesigning the prediction model of MPC,combining the speed controller with the current controller,establishing a non-cascading single closed loop speed-current controller based on MPC,and giving The design method.By constructing the simulation models of the above two structures,the dynamic response capability of the PMSM and the computing power of the MPC controller are compared and analyzed.Then,according to the influence of the accuracy of the model parameters on the predictive control strategy of the single closed-loop model,the dynamic response of PMSM under the deviation of stator resistance,stator inductance,stator flux and moment of inertia is given,and different parameter pairs are analyzed.The influence law of the MPC controller.In order to improve the anti-parameter perturbation ability of the single-closed-loop model predictive controller,a design method of the disturbance observer is proposed according to the Kalman filter(KF),and the design method of the explicit model predictive control(EMPC)is given.The observer and the MPC controller form a feedback control structure.Based on the above theory,the simulation model is built to verify the ability of the disturbance observer to suppress parameter disturbance.Finally,a PMSM control hardware experimental platform with DSP28335 was built as the core.The experimental results show that the single-loop EMPC has better dynamic response capability and less computational burden than PI control.And because of the increase of the disturbance observer,the parameter disturbance problem is improved,and the robustness of the PMSM control system is improved. |
