Research On Model-free Predictive Fault-tolerant Control For PMSM

Permanent magnet synchronous motor(PMSM)has been widely investigated and applied in rail transit due to its advantages,such as high efficiency,high power density,high torque-current ratio and wide speed range.At the same time,with the rapid improvement of microcontrollers performance,model predictive control is considered a highly promising alternative to PMSM high-performance control scheme based on traditional vector control.However,model predictive control relies on the motor predictive model.With complex and changeable traction conditions,the resistance,inductance and other parameters of PMSM are easily perturbed by external influences,and the permanent magnet(PM)demagnetization faults in PMSM easily occur.There exist many influencing factors causing model mismatches,therefore prediction error is generated and control performance decrease in model predictive control.Based on this problem,this thesis takes PMSM as the research object.In order to achieve robust control of parameter perturbations such as resistance and inductance and fault-tolerant control of demagnetization faults,a study on model-free fault-tolerant predictive control of PMSM is carried out.The main contributions are as follows:Aiming at the problem of prediction error caused by predictive model mismatches,the parameter perturbation is considered as main influencing factor of model mismatches in this thesis,and the main parameters such as resistance,inductance,and PM flux linkage are selected conduct a research.The influence of these three parameters on the prediction error are analysized,respectively.The theoretical analysis and simulation verification are carried out.From the perspective of theory and simulation,the influence of parameter mismatches on the stability of the system are revealed.The above analysis and research on model mismatches lays the foundation for the following improvement of model predictive control scheme.To solve the performance degradation of traditional finite control set model predictive control(FCS-MPC)for motor parameters perturbation and PM demagnetization faults,this thesis presents a finite control set model-free predictive fault-tolerant control(FCS-MFPFTC)method for PMSM current control.Firstly,according to a novel ultra-local model(ULM)of PMSM based on system input and output data,a FCS-MFPFTC controller for PMSM current loop is designed.Then,the sliding mode observer is used to estimate the unknown part h in the novel ULM of PMSM.Compared with the conventional FCS-MPC method,the experimental results show that the proposed method proves to be stronger robust and fault-tolerant to motor parameters perturbation and PM demagnetization faults.To solve the performance degradation of the PI control still used for the speed loop in the presented FCS-MFPFTC strategy with parameters perturbation,this thesis presents a model-free predictive fault-tolerant control(MFPFTC)method for the current loop and speed loop of a PMSM drive system.Firstly,the predictive control theory is combined with model-free control theory,the finitecontrol-set model-free predictive fault-tolerant current controller(FCSMFPFTCC)is designed based on the novel ULM in the current loop,and the model-free deadbeat predictive fault-tolerant speed controller(MFDPFTSC)is designed based on the novel ULM in the speed loop.Then,the unknown parts of the novel ULM is estimated by the designed extended sliding mode observer(ESMO).The experimental results show that the proposed MFPFTC method has better transient and steady-state performance and stronger robustness.And the observation accuracy of the ESMO is higher than that of the conventional SMO.Thus,the presented method reduces the dependence of the conventional predictive control on the accurate model,suppresses the influence of the model mismatch to the control system and realizes the fault-tolerant control of the PM demagnetization faults.