Research On Key Technologies Of Model-free Predictive Control For Permanent Magnet Synchronous Motor

Permanent magnet synchronous motor has the advantages of high efficiency,high power density and high reliability in the fields of robots and new energy vehicles.However,when the motor drive system is affected by uncertain factors such as parameter perturbation,degaussing fault and external disturbance,the traditional model predictive control algorithm cannot meet the requirements of high performance control such as current speed.Based on this problem,this paper takes the permanent magnet synchronous motor drive system as the research object,and carries out a series of researches around the model-free predictive control strategy of permanent magnet synchronous motor.First of all,this paper briefly introduces the basic structure and working principle of permanent magnet synchronous motor,and establishes the mathematical model of permanent magnet synchronous motor in different coordinate systems.In order to solve the problem that the traditional model predictive control reduces the control performance of the system when the motor parameters are not matched,a model-free predictive current control algorithm is proposed.By establishing the super local model of permanent magnet synchronous motor and combining model predictive control with model-free control,a model-free predictive controller is designed.At the same time,the unknown part of the hyperlocal model is estimated by online parameter identification,and the effectiveness of the proposed algorithm is verified by Simulink simulation.Secondly,in order to further solve the problem of the performance degradation of the control system,the hyperlocal model is improved into a new hyperlocal model to separate the linear part and the nonlinear part in the unknown disturbance of the motor.Based on modelfree predictive control and beat free control,a model-free beat free predictive current controller is designed to compensate the one-beat delay of voltage vector output.A sliding mode observer is introduced to accurately estimate the unknown part of the model.The stability of the sliding mode observer is proved by Lyapunov stability theory.The simulation and experimental results show that the proposed algorithm improves the transient performance of the permanent magnet synchronous motor when the parameters are mismatched and improves the anti-interference ability of the system.Finally,in order to further improve the robustness of the system,a model-free beat free control algorithm was introduced into the speed ring of the permanent magnet synchronous motor drive system,and a model-free beat free predictive speed controller was designed.An improved sliding mode observer is constructed on the basis of the sliding mode observer to reduce the chattering phenomenon.The improved sliding mode observer is also applied to the model-free beat prediction tach-current controller to estimate the unknown part of the new hyperlocal model.Simulation and experimental results show that the proposed algorithm has better transient performance and stronger robustness,gets rid of the dependence of predictive control on high-precision motor model,and restrains the influence of model mismatch control system.