State and parameter estimation of induction machines

Estimation of the parameters of an induction machine is very important in point of the performance prediction, simulation analysis and control application. In this study, it is presented the application of the Kalman filter to estimate conjointly the states and parameters of a three phased squirrel-cage induction motor fed from a sinusoidal, six step and PWM sources at different times using measurements of the stator voltages and currents and the rotor speed. A feature of the Kalman filter, not present in other statistical filters, is its ability to adjust its ownparameters according to the statistics of the measurements from each sample. In other filtering methods, the percentage of the error between the measured and expected data used to adjust the model parameters is kept as a constant for the entire sample sequence, or is adjusted by the programmer. However, the Kalman filter allows this percentage to change automatically for the best performance. When the measurement data changes instantaneously in case of six step and PWM waveforms, the sampling frequency should be chosen at high values. However, filter demands a higher computational period. For all the supply voltages, filter shows very high performance to estimate both states and parameters. Key Words: Induction Machine, Induction Motor Simulation, Vektör Control, Extended Kalman Filter, State Variables, Parameter Estimation VI