Robust speed sensorless fuzzy control of the induction machine drive with adaptation of the rotor time constant supplied by photovoltaic solar energy

In this paper, we studied the vector control, by orientation of rotor-flux by using fuzzy regulators for an induction machine without speed sensor with adaptation of rotor resistance uzing method based on calculation of the reactive power of the machine with permanent rate with fuzzy Regulator supplied by photovoltaic solar energy. The speed is estimated by using the adaptive method with model of reference (MRAS). This method consists in working out two models one of reference and the control adjustable one for the estimate of two components of stator flux starting from the measurement of the currents and stator voltages. The estimated speed is obtained by cancelling the difference between stator-flux of the model of reference and those of the adjustable model. Very satisfactory results of simulation are presented at the end of this paper.

[1]  Hong Yu Wang,et al.  Speed Sensorless Vector Control System of Induction Motor , 2012 .

[2]  Ron J. Patton,et al.  Fault-Tolerant Control , 2000, Encyclopedia of Systems and Control.

[3]  A. F. Stronach,et al.  Fuzzy control of AC drives , 1994 .

[4]  Tadashi Fukao,et al.  Robust speed identification for speed sensorless vector control of induction motors , 1993, Conference Record of the 1993 IEEE Industry Applications Conference Twenty-Eighth IAS Annual Meeting.

[5]  Hansruedi Bühler.  Réglage par logique floue , 1994 .

[6]  Seung-Ki Sul,et al.  Speed sensorless vector control of induction motor using extended Kalman filter , 1994 .

[7]  M.S. Boucherit,et al.  Robust position control of machine tools with a strategy of linearization by state return using fuzzy regulators , 2006, International Symposium on Power Electronics, Electrical Drives, Automation and Motion, 2006. SPEEDAM 2006..

[8]  Ron J. Patton,et al.  Fault-Tolerant Control: The 1997 Situation , 1997 .

[9]  M. Staroswiecki.  Actuator faults and the linear quadratic control problem , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[10]  P.K.Saha,et al.  Solar Panel Maximum Power Point Tracker for Power Utilities , 2014 .

[11]  Ebrahim Mamdani,et al.  Applications of fuzzy algorithms for control of a simple dynamic plant , 1974 .

[12]  H. Nakano,et al.  Sensor less field oriented control of an induction motor using an instantaneous slip frequency estimation method , 1988, PESC '88 Record., 19th Annual IEEE Power Electronics Specialists Conference.