Title :
Modeling and RFOC of faulty three-phase IM using Extended Kalman Filter for rotor speed estimation
Author :
Jannati, M. ; Anbaran, S.A. ; Alsofyani, I.M. ; Idris, N.R.N. ; Aziz, M.J.A.
Author_Institution :
UTM-PROTON Future Drive Lab., Univ. Teknol. Malaysia, Skudai, Malaysia
Abstract :
This research discusses d-q model and Rotor Flux-Oriented Control (RFOC) technique for faulty three-phase Induction Motor (three-phase IM when one of the stator phases is opened). In the controlling technique, two transformation matrixes are applied to the equations of faulty three-phase IM. As a result, the equations of faulty three-phase IM become similar to the balanced IM. Therefore, by employing some modifications in the conventional block diagram of the balanced IM, faulty motor control is possible. Additionally, for high performance vector control of the faulty IM, an Extended Kalman Filter (EKF) is used for motor speed estimation. Simulation results demonstrate the validity and applicability of this technique to improve performance of the faulty IM.
Keywords :
Kalman filters; angular velocity control; induction motors; machine vector control; matrix algebra; nonlinear filters; phase control; rotors; stators; EKF; RFOC technique; extended Kalman filter; faulty motor control; faulty three-phase IM; induction motor; rotor flux-oriented control technique; rotor speed estimation; stator phase; transformation matrix; vector control; Circuit faults; Equations; Estimation; Mathematical model; Rotors; Stator windings;
Conference_Titel :
Power Engineering and Optimization Conference (PEOCO), 2014 IEEE 8th International
Conference_Location :
Langkawi
Print_ISBN :
978-1-4799-2421-9
DOI :
10.1109/PEOCO.2014.6814438