Motor rotor resistance identification based on Elman neural network

Motor parameter identification is problem must be faced by high performance variable frequency speed adjustment system include Vector Control. Explore new effective parameter identification method possess vast theoretical and practical meanings. Motor´s mathematical model has the character of high order, nonlinear and complicate coupling, the parameter change with the work state is difficult to describe with a definite function. Rotor resistance is identified with Elman neural network which has the ability of function approximation and unique feedback. The simulation result is validated by the parameter obtained with other methods and shows some advantages. It has some reference meaning to more extend motor parameter identification.