Sensorless Speed Based on MRAS with Tuning of IP Speed Controller in FOC of Induction Motor Drive Using PSO
In this paper, a field oriented control (FOC) induction motor drive is presented. In order to eliminate the speed sensor, an adaptation algorithm for tuning the rotor speed is proposed. Based on the Model Reference Adaptive System (MRAS) scheme, the rotor speed is tuned to obtain an exact FOC induction motor drive. The reference and adjustable models, developed in stationary stator reference frame, are used in the MRAS scheme to estimate induction rotor speed from measured terminal voltages and currents. The Integral Proportional (IP) gains speed controller are tuned by a modern approach that is the Particle Swarm Optimization (PSO) algorithm in order to optimize the parameters of the IP controller. The use of PSO as an optimization algorithm makes the drive robust, with faster dynamic response, higher accuracy and insensitive to load variation. The proposed algorithm has been tested by numerical simulation, showing the capability of driving load.
[1] V. Vasic, S. Vukosavic, "Robust MRAS-based algorithm for stator
resistance and rotor speed identification," IEEE Power Engineering
Review , pp. 39-41, Nov. 2001.
[2] S. Meziane, R. Toufouti, H. Benalla, "MRAS based speed control of
sensorless induction motor drives ," ICGST-ACSE Journal, Vol. 7, Issue
1, pp. 43-50, May 2007.
[3] Y. Agrebi, M. Triki, Y. Koubaa, M. Boussak, " Rotor speed estimation
for indirect stator flux oriented induction motor drive based on MRAS
scheme," Journal of Electrical Systems, Vol. 3, No 3, pp. 131-143, 2007.
[4] I. K. Bousserhane, A. Hazzab, M. Rahli, B. Mazari, M. Kamli, "Position
control of linear induction motor using an adaptive fuzzy integral -
backstepping controller ," Serbian Journal of Electrical Engineering,
Vol. 3, No. 1, pp. 1-17, June 2006.
[5] A. S. Elwer, "A novel technique for tuning PI-controllers in induction
motor drive systems for electric vehicle applications," Journal of Power
Electronics, Vol. 6, No. 4, pp. 322-329, Oct. 2006.
[6] J. Kennedy, R. Eberhart: "Particle swarm optimization", IEEE
Transactions, pp. 1942-1948, 1995.
[7] F. J. Lin, L. T. Teng, J. W. Lin, and S. Y. Chen, "Recurrent functional-
link-based fuzzy-neural-network-controlled induction-generator system
using improved particle swarm optimization," IEEE Transactions on
Industrial Electronics, Vol. 56, No. 5, pp. 1557-1577, May 2009.
[8] A. Chaari, M. Soltani, M. Gossa, "Comparative study between the
conventional regulators and fuzzy logic controller: application on the
induction machine ," International Journal of Sciences and Techniques
of Automatic control & computer engineering IJ-STA, Vol. 1, No 2, pp.
196−212, Dec. 2007.
[9] A. Mechernene, M. Zerikat and M. Hachlef, "Fuzzy speed regulation for
induction motor associated with field-oriented control," International
Journal of Sciences and Techniques of Automatic control & computer
engineering IJ-STA, Vol. 2, No 2, pp. 804−817, Dec. 2008.
[10] A. BEN ALI, A. KHEDHER, M. F. MIMOUNI, R. DHIFAOUI
"Torque maximization and sensorless control of induction motor in a
flux weakening region," International Journal of Sciences and
Techniques of Automatic control & computer engineering IJ-STA, Vol.
3, No 1, pp. 972−985, July 2009.
[11] M. MESSAOUDI, H. KRAIEM, M. BEN HAMED, L. SBITA and M.
N. ABDELKRIM, "A robust sensorless direct torque control of
induction motor based on MRAS and extended kalman filter," Leonardo
Journal of Sciences, Issue 12, January-June 2008, pp. 35-56.
[12] A. Abbou and H. Mahmoudi, "Performance of a sensorless direct torque
flux control strategy for induction motors associated to the three levels
NPC converter used in electrical vehicles," International Journal of
Sciences and Techniques of Automatic & computer engineering IJ-STA,
Vol. 2, No 2, pp. 790-803, Dec. 2008.
[13] M. PADMA LALITHA,V. C. VEERA REDDY, V.USHA, "Optimal
DG placement for minimum real power loss in radial distribution
systems using PSO," Journal of Theoretical and Applied Information
Technology, pp. 107- 116, 2010.
[14] R.C Eberhart. and Y. Shi, "Comparing inertial weights and constriction
factor in particle swarm optimization," in Proceeding of the
International Congress on Evaluationing Computation, pp. 84-88, 2000.
[15] B. ALLAOUA, B. GASBAOUI, B. MEBARKI, "Setting up PID DC
motor speed control alteration parameters using particle swarm
optimization strategy," Leonardo Electronic Journal of Practices and
Technologies, Issue 14, January-June 2009, pp. 19-32.
[1] V. Vasic, S. Vukosavic, "Robust MRAS-based algorithm for stator
resistance and rotor speed identification," IEEE Power Engineering
Review , pp. 39-41, Nov. 2001.
[2] S. Meziane, R. Toufouti, H. Benalla, "MRAS based speed control of
sensorless induction motor drives ," ICGST-ACSE Journal, Vol. 7, Issue
1, pp. 43-50, May 2007.
[3] Y. Agrebi, M. Triki, Y. Koubaa, M. Boussak, " Rotor speed estimation
for indirect stator flux oriented induction motor drive based on MRAS
scheme," Journal of Electrical Systems, Vol. 3, No 3, pp. 131-143, 2007.
[4] I. K. Bousserhane, A. Hazzab, M. Rahli, B. Mazari, M. Kamli, "Position
control of linear induction motor using an adaptive fuzzy integral -
backstepping controller ," Serbian Journal of Electrical Engineering,
Vol. 3, No. 1, pp. 1-17, June 2006.
[5] A. S. Elwer, "A novel technique for tuning PI-controllers in induction
motor drive systems for electric vehicle applications," Journal of Power
Electronics, Vol. 6, No. 4, pp. 322-329, Oct. 2006.
[6] J. Kennedy, R. Eberhart: "Particle swarm optimization", IEEE
Transactions, pp. 1942-1948, 1995.
[7] F. J. Lin, L. T. Teng, J. W. Lin, and S. Y. Chen, "Recurrent functional-
link-based fuzzy-neural-network-controlled induction-generator system
using improved particle swarm optimization," IEEE Transactions on
Industrial Electronics, Vol. 56, No. 5, pp. 1557-1577, May 2009.
[8] A. Chaari, M. Soltani, M. Gossa, "Comparative study between the
conventional regulators and fuzzy logic controller: application on the
induction machine ," International Journal of Sciences and Techniques
of Automatic control & computer engineering IJ-STA, Vol. 1, No 2, pp.
196−212, Dec. 2007.
[9] A. Mechernene, M. Zerikat and M. Hachlef, "Fuzzy speed regulation for
induction motor associated with field-oriented control," International
Journal of Sciences and Techniques of Automatic control & computer
engineering IJ-STA, Vol. 2, No 2, pp. 804−817, Dec. 2008.
[10] A. BEN ALI, A. KHEDHER, M. F. MIMOUNI, R. DHIFAOUI
"Torque maximization and sensorless control of induction motor in a
flux weakening region," International Journal of Sciences and
Techniques of Automatic control & computer engineering IJ-STA, Vol.
3, No 1, pp. 972−985, July 2009.
[11] M. MESSAOUDI, H. KRAIEM, M. BEN HAMED, L. SBITA and M.
N. ABDELKRIM, "A robust sensorless direct torque control of
induction motor based on MRAS and extended kalman filter," Leonardo
Journal of Sciences, Issue 12, January-June 2008, pp. 35-56.
[12] A. Abbou and H. Mahmoudi, "Performance of a sensorless direct torque
flux control strategy for induction motors associated to the three levels
NPC converter used in electrical vehicles," International Journal of
Sciences and Techniques of Automatic & computer engineering IJ-STA,
Vol. 2, No 2, pp. 790-803, Dec. 2008.
[13] M. PADMA LALITHA,V. C. VEERA REDDY, V.USHA, "Optimal
DG placement for minimum real power loss in radial distribution
systems using PSO," Journal of Theoretical and Applied Information
Technology, pp. 107- 116, 2010.
[14] R.C Eberhart. and Y. Shi, "Comparing inertial weights and constriction
factor in particle swarm optimization," in Proceeding of the
International Congress on Evaluationing Computation, pp. 84-88, 2000.
[15] B. ALLAOUA, B. GASBAOUI, B. MEBARKI, "Setting up PID DC
motor speed control alteration parameters using particle swarm
optimization strategy," Leonardo Electronic Journal of Practices and
Technologies, Issue 14, January-June 2009, pp. 19-32.
@article{"International Journal of Electrical, Electronic and Communication Sciences:59400", author = "Youcef Bekakra and Djilani Ben attous", title = "Sensorless Speed Based on MRAS with Tuning of IP Speed Controller in FOC of Induction Motor Drive Using PSO", abstract = "In this paper, a field oriented control (FOC) induction motor drive is presented. In order to eliminate the speed sensor, an adaptation algorithm for tuning the rotor speed is proposed. Based on the Model Reference Adaptive System (MRAS) scheme, the rotor speed is tuned to obtain an exact FOC induction motor drive. The reference and adjustable models, developed in stationary stator reference frame, are used in the MRAS scheme to estimate induction rotor speed from measured terminal voltages and currents. The Integral Proportional (IP) gains speed controller are tuned by a modern approach that is the Particle Swarm Optimization (PSO) algorithm in order to optimize the parameters of the IP controller. The use of PSO as an optimization algorithm makes the drive robust, with faster dynamic response, higher accuracy and insensitive to load variation. The proposed algorithm has been tested by numerical simulation, showing the capability of driving load.
", keywords = "Induction motor drive, field oriented control, model reference adaptive system (MRAS), particle swarm optimization (PSO).", volume = "5", number = "12", pages = "1814-6", }
