Improved Moment of Inertia Identification of MRAS Based on Load Disturbance Observation
The traditional model reference adaptive system(MRAS)cannot meet the requirements of identi-fication accuracy and convergence speed at the same time when the load of AC servo motor changes rapidly.In view of this,an improved MRAS moment of inertia identification strategy based on sliding window filter is proposed.First,the curvature model(CM)is used to predict the load disturbance of the motor in real time,and then the traditional MRAS method is improved.Based on the sliding window filter principle,the variable gain mechanism is set up to determine the basis,so that the system automatically adjusts the gain coefficient in the adaptive rate when the load changes,ensuring that the moment of inertia is quickly and accurately iden-tified.Finally,the proposed method is verified by simulation and real platform construction.The results show that the proposed method not only has high identification accuracy,but also has fast convergence speed,which overcomes the shortcomings of traditional methods and shows excellent dynamic performance.
NETL
NSTL
万方数据
维普
