The advancement of sophisticated power electronics technology and high expectation of sensing reliability attribute to the rapid deployment of sensorless-control of AC motor drives. The purpose of this thesis is to provide the comparative studies of the extended Kalman filter (EKF), the fault tolerant extended Kalman filter (FTEKF), and the unscented Kalman filter (UKF)-based sensorless direct torque control approaches for permanent magnet AC motor (PMAC) and induction motor (IM) drives to improve Kalman filtering based state-estimation performances during external disturbances, noise and measurement failures. The proposed fault tolerant Kalman filtering control algorithm is robust to modeling uncertainties and sensing failures. Comparative of computer simulation studies and hardware implementations results have shown that the proposed second-order fault tolerant Kalman filter (SOFTEKF) provide superior state-estimation performance improvements in comparison with the unscented Kalman filter and traditional extended Kalman filter for sensorless direct torque control applications of AC motor drives.
|Commitee:||Leander, Robert, York, Tim|
|School:||Southern Illinois University at Edwardsville|
|School Location:||United States -- Illinois|
|Source:||MAI 58/03M(E), Masters Abstracts International|
|Subjects:||Engineering, Electrical engineering|
|Keywords:||EKF, Fault, IM, SPMSM, UKF|
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