Fuzzy Logic Speed Control for Sensorless Indirect Field Oriented of Induction Motor Using an Extended Kalman Filter


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Abstract


In this paper, we present the speed sensorless of indirect field oriented control (IFOC) of induction motor (IM). The speed estimator has been designed using extended Kalman filter technique (EKF). According to this method, the rotor speed is obtained from the directly measurable stator voltages and currents. A fuzzy logic controller (FLC) used for the speed and sliding mode controllers (SMC) used for stator currents control to allow a good performance and robustness against the load disturbances. Simulation results are illustrated and demonstrate the effectiveness of the proposed strategy.
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Keywords


Speed Sensorless; Indirect Field Oriented Control; Induction Motor; Extended Kalman Filter; Fuzzy Logic Control; Sliding Mode Control

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References


A. Abbou, T. Nasser, H. Mahmoudi, M. Akherraz, and A. Essadki, Induction motor controls and implementation using dspace, WSEAS Transactions on Systems and Control, Vol. 7:26-35, 2012.

H. Nakano, and I. Takahashi, Sensorless field oriented control of an induction motor using an instantaneous slip frequency estimation method, IEEE Power Electronics Specialists Conference, Vol. 2, pp. 847-854, 11-14 April 1988.

T. Ohtani, N. Takada, and K. Tanaka, Vector control of induction motor without shaft encoder, IEEE industry Applications Society Annual Meeting Conference Record, Vol. 1, pp. 500-507, 1-5 Oct, 1989.

LA. Zadeh, Fuzzy sets, Information and Control, Vol. 8:338-353, 1965.

C. Vecchio, Sliding mode control: theoretical developments and applications to uncertain mechanical system, Degli Studi Pavia University.

YR. Kim, SK. Sul, and MH. Park, Speed sensorless vector control of induction motor, using extended Kalman filter, IEEE Transactions on Industry Applications, Vol. 30(Issue 5):1225-1233-1994.

KL. Shi, TF. Chan, Y.K. Wong, and S. L. Ho, Speed estimation of an induction motor drive using an optimized extended Kalman filter, IEEE Transactions on Industrial Electronics, Vol. 49:124-133, 2002.

V. Peter, Sensorless vector and direct torque control, Oxford New York Tokyo, Oxford University Press, 1998.

V. Utkin, Variable structure systems with sliding modes, IEEE Transactions on Automatic Control, Vol .22(Issue 2):212–222, 1977.

JJE. Slotine, W. Li, Applied nonlinear control, New Jersey, Prentice-Hall, Inc, 1991.

B. Sahu, KB. Mohanty, S. Pati, A comparative study on fuzzy and PI speed controllers for field-oriented induction motor drive, International Conference on Industrial Electronics, Control and Robotics 2010, pp. 191-196, 27-29 Dec, 2010.

K. Yahia, S.E. Zouzou, F. Benchabane and D. Taibi, Comparative study of an adaptive Luenberger observer and extended Kalman filter for a sensorless direct vector control of induction motor, Vol. 50:99-107, 2009.

M. M. Krishan, Fuzzy Sliding Mode Control with MRAC Technique Applied to an Induction Motor Drives, (2008) International Review of Automatic Control (IREACO), 1 (1), pp. 42-48.

Lalalou, R., Bahi, T., Bouzekri, H., Sensorless indirect vector controlled induction motor using fuzzy logic control of speed estimation and stator resistance adaptation, (2010) International Review on Modelling and Simulations (IREMOS), 3 (3), pp. 325-330.

Salehi, S.J., Manoochehri, M., A nonlinear sliding mode control of induction motor based on second order speed and flux sliding mode observer, (2011) International Review on Modelling and Simulations (IREMOS), 4 (3), pp. 1057-1065.

Boulghasoul, Z., Elbacha, A., Elwarraki, E., Real time implementation of fuzzy adaption mechanism for MRAS sensorless indirect vector control of induction motor, (2011) International Review of Electrical Engineering (IREE), 6 (4), pp. 1636-1653.

Aydin, M., Gokasan, M., Bogosyan, S., Comparison of two EKF based observers optimized online by both simulated annealing and Big Bang-Big Crunch methods for sensorless estimations in Induction Motor, (2011) International Review on Modelling and Simulations (IREMOS), 4 (5), pp. 2111-2121.


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