Deadbeat Current Predictive Control Of Permanent Magnet Synchronous Motor Based On Parameter Identification

Permanent magnet synchronous motor has been widely used in high precision servo control field because of its fast dynamic response,high steady-state precision and wide speed range.The dynamic and steady-state performance of the motor is depended on the current inner loop,but traditional current loop control strategy can not meet the requirements of the motor control performance Thus,new control strategies such as predictive control are used in the control of the motor current loop.Firstly,,In this paper,the mathematical model of the surface-mount permanent magnet synchronous motor is simplified,and its mathematical model is deduced in the three-phase stationary coordinate system.The CLARK and PARK transform matrix are deduced based on the conservation principle of magnetic potential,The mathematical model of the three phase permanent magnet synchronous motor under d and q axis is obtained,and the decoupling of the motor excitation component and the torque component is realized.The mathematical model is discretized by the first-order Taylor formula,and the motor’s predictive control model is obtained.Secondly,the principle of deadbeat current prediction is introduced.The performance of the predictive control depends on the accuracy of the motor parameters.Therefore,the relationship between the motor parameter error and the steady-state performance of the predictive control is analyzed.In order to enhance the robustness of the control system to the inductive parameters,a robust current prediction control algorithm is adopted to adjust the size of the weight coefficient to adjust the size of the control system.Stable range,but the change in the weight coefficient will affect the control system bandwidth,resulting in the dynamic response of the current slowdown,in order to maximize the performance of predictive control,we need to combine these two algorithms to learn from each other.Then,in order to eliminate the current steady-state error caused by the motor parameter error,the inductance and flux linkage of the motor are identified by the model reference adaptive method,and the error of the model parameters is corrected in real time by the identification value of the motor parameters.And the on-line identification strategy based on inductance parameter is proposed.The robust control algorithm is used to improve the stability of the control system when the inductance error is large,and when the inductance parameter converges to the real value,switching back to the traditional deadbeat current prediction control to improve its dynamic response,so that the stability of the control system is improved while maintaining its dynamic response speed unchanged.Finally,permanent magnet synchronous motor drive system is designed based on TMS320F28335 and hardware design principles were introduced.Through experiments to further verify the relationship between deadbeat current predictive control performances and motor parameters,robust prediction control algorithm,model reference adaptive parameter identification algorithm and the on-line switching strategy proposed in this paper.