The Sensorless Control Research Of PMLSM Based On Double Forgotten Kalman Filter

Permanent magnet linear synchronous motor(PMLSM)due to a series advantages of its simple structure,good dynamic performance,high force index,good controllability,infinite hoisting height,can be more capsules and so on,getting wide attention both home and abroad by the researchers.The existence of the traditional mechanical sensor will increase the system cost,make maintenance complex,running accuracy decline,some places can't install,etc.So,without position sensor of PMLSM,become a focus in the study of this article.Firstly,the power-angle feature is one of the most important feature of PMLSM,it can through the changing of the power-angle to adapt to the different loads.The traditional power-angle feature of rotating motor is a simple sine function,because the ends are open,the air gap is big,the running frequency is low,the end leakage is serious and the end effect should not be neglected,so it is likely to occur step dangerous,etc.Therefore,in order to better control of PMLSM,it is particularly important to study the power-angle feature under different power frequency.Secondly,with EKF(Extend Kalman Filter)to estimate the position of PMLSM(Permanent magnet linear synchronous motor),under the model is not accurate,the noise properties is uncertain,it leads to the precision of estimation is not high and the problem of filtering divergence,so DFKF(Double forgetting kalman filter)method was proposed to used for PMLSM without position sensing control research.Adaptive fading factor on the basis of EKF was introduced to achieve the first forgetting,then the Sage-Husa adaptive filter algorithm was introduced to realize the second forgetting,it can effectively reduce the model error,improve the filter accuracy.The studies show that in the estimation of EKF,it occurs to filtering divergence,but no matter in synchronous speed changing or load mutation,DFKF diminishing according to the law of sine,before the load mutation,the stable error is 0.469%,the maximum error of the estimated speed is within 0.943% after,the final speed estimation error control in the vicinity of 0.167%,the error is small,the longer time of the simulation,the better of the effect,finally realizes the complete tracking,and has good robustness.