Vector control of induction motors by using EKF and LFK

The knowledge of the rotor flux space-vector position is essential to implement the direct field-oriented control strategy to induction motor drives. In this paper a delayed state Kalman filter has been used to estimate the rotor flux position and the parameters of an induction motor. The main advantage of the proposed algorithm may be resumed as follows: good performance in transient conditions; high convergence rate; very low steady-state errors; optimal rejection of measurement noise. In this paper is also proposed the linear Kalman filter (LKF) to estimate the equivalent disturbance. It allows an optimal rejection of load torque. variations of mechanical parameters, process nonlinearities and inaccuracy in the process modelling. The simulation results have shown that the estimation algorithm has a fast convergence rate and tracks the changes in the equivalent disturbance very well. Thanks to the joined action of the EKF and LKF-based algorithms the desired dynamic performances of the drive can be preserved in every operating condition