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Frontiers in Energy

ISSN 2095-1701

ISSN 2095-1698(Online)

CN 11-6017/TK

Postal Subscription Code 80-972

2018 Impact Factor: 1.701

Front Energ    2014, Vol. 8 Issue (1) : 81-89    https://doi.org/10.1007/s11708-014-0295-9
RESEARCH ARTICLE
Assessment of a fuzzy logic based MRAS observer used in a photovoltaic array supplied AC drive
Bhavnesh KUMAR1(), Yogesh K CHAUHAN1, Vivek SHRIVASTAVA2
1. School of Engineering, Gautam Buddha University, Greater Noida 201310, India; 2. Electrical Engineering Department, National Institute of Technology Delhi, Delhi 110077, India
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Abstract

In this paper a fuzzy logic (FL) based model reference adaptive system (MRAS) speed observer for high performance AC drives is proposed. The error vector computation is made based on the rotor-flux derived from the reference and the adaptive model of the induction motor. The error signal is processed in the proposed fuzzy logic controller (FLC) for speed adaptation. The drive employs an indirect vector control scheme for achieving a good closed loop speed control. For powering the drive system, a standalone photovoltaic (PV) energy source is used. To extract the maximum power from the PV source, a constant voltage controller (CVC) is also proposed. The complete drive system is modeled in MATLAB/Simulink and the performance is analyzed for different operating conditions.

Keywords induction motor drive      fuzzy logic (FL) control      model reference adaptive system (MRAS)      photovoltaic (PV) array      vector control     
Corresponding Author(s): KUMAR Bhavnesh,Email:kumar.bhavnesh34@gmail.com   
Issue Date: 05 March 2014
 Cite this article:   
Bhavnesh KUMAR,Yogesh K CHAUHAN,Vivek SHRIVASTAVA. Assessment of a fuzzy logic based MRAS observer used in a photovoltaic array supplied AC drive[J]. Front Energ, 2014, 8(1): 81-89.
 URL:  
https://academic.hep.com.cn/fie/EN/10.1007/s11708-014-0295-9
https://academic.hep.com.cn/fie/EN/Y2014/V8/I1/81
Fig.1  Block diagram of sensorless induction motor drive with MPPT assisted PV source
Fig.2  PV array equivalent circuit
Fig.3  FL-based MRAS speed observer
Fig.4  Fuzzy membership functions for inputs/output
Change in errorError
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Tab.1  Rule matrix for FLC
Fig.5  Current-voltage () curves for designed PV array
(a) With multiple insolation level; (b) with multiple temperature
Fig.6  DC-DC boost converter
(a) Duty ratio; (b) input and output voltage
Fig.7  Response of motor
(a) Rotor speed; (b) motor current; (c) motor torque
Fig.8  Boost converter
(a) Duty ratio; (b) input and output voltage
Fig.9  Response of motor
(a) Rotor speed; (b) motor torque
Fig.10  Fast varying insolation level
Fig.11  Boost converter
(a) Duty cycle; (b) input and output voltage
Fig.12  Response of motor
(a) Rotor speed; (b) motor torque
1 Elgendy M A, Zahawi B, Atkinson D J. Comparison of directly connected and constant voltage controlled photovoltaic pumping systems. IEEE Trans on Sustainable Energy , 2010, 1(3): 184-192
doi: 10.1109/TSTE.2010.2052936
2 Atlas H, Sharaf A M. A Photovoltaic array simulation model for Matlab-Simulink GUI environment. In: International Conference on Clean Electrical Power, Capri, Italy , 2007, 341-345
3 Vitorino M A, Beltrao de Rossiter Correa M, Jacobina C B, Lima A M N. An effective induction motor control for photovoltaic pumping. IEEE Transactions on Industrial Electronics , 2011, 58(4): 1162-1170
doi: 10.1109/TIE.2010.2054053
4 Kuo Y C, Liang T J, Chen J F. Novel maximum-power-point-tracking controller for photovoltaic energy conversion system. IEEE Transactions on Industrial Electronics , 2001, 48(3): 594-601
doi: 10.1109/41.925586
5 Wai R J. Hybrid control for speed sensorless induction motor drive. IEEE Transactions on Fuzzy Systems , 2001, 9(1): 116-138
doi: 10.1109/91.917119
6 Bose B K. Modern Power Electronics and AC Drives. Prentice Hall , 2002.
7 Cardenas R, Pena R. Sensorless vector control of induction machines for variable-speed wind energy applications. IEEE Transactions on Energy Conversion , 2004, 19(1): 196-205
doi: 10.1109/TEC.2003.821863
8 Gadoue S M, Giaouris D, Finch J W. MRAS sensorless vector control of an induction motor using new sliding-mode and fuzzy-logic adaptation mechanisms. IEEE Transactions on Energy Conversion , 2010, 25(2): 394-402
doi: 10.1109/TEC.2009.2036445
9 Xu Z, Shao C, Feng D. An MRAS method for sensorless control of induction motor over a wide speed range. Journal of Control Theory and Applications , 2011, 9(2): 203-209
doi: 10.1007/s11768-011-8202-y
10 Vasic V, Vukosavic S N, Levi E. A stator resistance estimation scheme for speed sensorless rotor flux oriented induction motor drives. IEEE Transactions on Energy Conversion , 2003, 18(4): 476-483
doi: 10.1109/TEC.2003.816595
11 Orlowska-Kowalska T, Dybkowski M. Stator-Current-Based MRAS Estimator for a Wide Range Speed-Sensorless Induction-Motor Drive. IEEE Transactions on Industrial Electronics , 2010, 57(4): 1296-1308
doi: 10.1109/TIE.2009.2031134
12 Maiti S, Chakraborty C, Hori Y, Ta M C. A stable back-EMF MRAS-based sensorless low speed induction motor drive insensitive to stator resistance variation. IEE Proceedings Electric Power Application , 2004, 151(6): 685-693
13 Maiti S, Chakraboty C, Hori Y, Ta M C. Model reference adaptive controller-based rotor resistance and speed estimation techniques for vector controlled induction motor drive utilizing reactive power. IEEE Transactions on Industrial Electronics , 2008, 55(2): 594-601
doi: 10.1109/TIE.2007.911952
14 Iacchetti M F, Carmeli M S, Castelli Dezza F, Perini R. A speed sensorless control based on a MRAS applied to a double fed induction machine drive. Electrical Engineering , 2010, 91(6): 337-345
doi: 10.1007/s00202-009-0144-8
15 Salem Z M, Khater M M, Kalilah S A, Mahmoud S A. Fuzzy logic based mras for sensorless induction motor drive. In: Eleventh International Middle East Power Systems Conference, El-Minia, Egypt , 2006, 427-433
16 Gümü? B, ?zdemir M. Sensorless vector control of a Permanent magnet synchronous motor with fuzzy logic observer. Electrical Engineering , 2006, 88(5): 395-402
doi: 10.1007/s00202-005-0301-7
17 Douiri M R, Cherkaoui M. Learning fuzzy controller and extended Kalman filter for sensorless induction motor robust against resistance variation. Frontiers of Electrical and Electronic Engineering , 2012, 7(3): 347-355
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