In recent years,with the development of control strategies for permanent magnet synchronous motor,model predictive control has found an increasingly wide application in PMSM.The narrowing cycle difference between speed loop and current loop used in traditional PMSM has highlighted the unique advantage for single-loop MPC(SMPC).By merging the two separate loops into a single one,SMPC enables a simplified system structure and better control performance.The research on SMPC has certain theoretical and application significance.Firstly,based on the model predictive control theory,single-loop MPC for PMSM system is designed and analyzed in detail.Then,to ensure saturation and constraints simultaneously,practical constraints are considered to optimize the SMPC.The MATLAB/Simulink simulation results show that the method proposed can improve the control performance within control range.Secondly,periodic characteristic of PMSM torque ripple is analyzed and mathematical modeling is established.To minimize the torque ripple of PMSM,output speed error model and control rate error model are introduced into predictive control model,thus iterative learning and model predictive control are integrated into iterative predictive algorithm and applied to PMSM.Simulations on PI control and iterative predictive control are compared and the results prove the latter equips with both faster response and higher steady-state accuracy,which validate the availability.Finally,with the platform of TMS320F2812 DSP,experiments on single-loop model predictive controlled PMSM are carried out,validating its advantages in dynamic characteristics,static error and anti-disturbance ability. |