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http://yadda.icm.edu.pl:80/baztech/element/bwmeta1.element.baztech-d460a63f-a452-4206-a515-2fb3030675cd

Czasopismo

Przegląd Elektrotechniczny

Tytuł artykułu

Implementation of a Neuro-Fuzzy Direct Torque and Reactive Power Control for Doubly Fed Induction Motor

Autorzy Jacomini, R. V.  Rocha, C. M.  Altuna, J. A. T.  Azcue-Puma, J. L.  Capovilla, C. E.  Sguarezi Filho, A. J. 
Treść / Zawartość http://pe.org.pl/
Warianty tytułu
PL Zastosowanie systemu neurofuzzy do sterowania momentem i mocą bierną w podwójnie zasilanym silniku indukcyjnym
Języki publikacji EN
Abstrakty
EN This paper proposes a Takagi-Sugeno neuro-fuzzy inference system for direct torque and stator reactive power control applied to a doubly fed induction motor. The control variables (d-axis and q-axis rotor voltages) are determined through a control system composed by a neuro-fuzzy inference system and a first order Takagi-Sugeno fuzzy logic controller. Experimental results are presented to validate the controller operation for variable speed under no-load and load conditions and stator reactive power variation under load condition. For this last validation, a PI controller is used to control the rotor speed, thereby its output is used to manipulate the torque in order to follow the demanded speed value.
W artykule opisano inferencyjny neuro-fuzzy system Takagi-Sugeno użyty do sterowania momentem i mocą bierną w podwójnie zasilanym silniku indukcyjnym. Przeprowadzono eksperymenty sterowania silnikiem obciążonym i nieobciążonym.
Słowa kluczowe
PL silnik indukcyjny   sterowanie momentem silnika   system neuro-fuzzy   moc bierna  
EN doubly fed induction machine   direct torque control   reactive power control   ANFIS   neuro-fuzzy control  
Wydawca Wydawnictwo SIGMA-NOT
Czasopismo Przegląd Elektrotechniczny
Rocznik 2014
Tom R. 90, nr 10
Strony 179--187
Opis fizyczny Bibliogr. 24 poz., rys., tab., wykr.
Twórcy
autor Jacomini, R. V.
autor Rocha, C. M.
autor Altuna, J. A. T.
autor Azcue-Puma, J. L.
autor Capovilla, C. E.
autor Sguarezi Filho, A. J.
Bibliografia
[1] F. Blaabjerg and F. Iov, Wind Power - A Power Soucer Now Enabled By Power Electronics, 9th Brasilian Power Electronics Conference, 2007.
[2] R. Datta and V.T. Rangathan, Variable-speed wind power generation using doubly fed wound rotor induction machine - a comparison with alternative schemes, IEEE Transactions on Energy Conversion, Vol. 17, N0. 3, Sep. 2002, pp. 414-421.
[3] P. Vas, Sensorless Vector and Direct Torque Control, Oxford University Press, 1998.
[4] Y. Kawabata, E. Ejiogu, and T. Kawabata, Vector-controlled double-inverter-fed wound-rotor induction motor suitable for highpower drives, IEEE Transactions on Industry Applications, Vol. 35, pp. 1058-1066, 1999.
[5] R. Datta and V.T. Ranganathan, Direct Power Control of Grid-Connected Wound Rotor Induction Machine Without Rotor Position Sensors, IEEE Transactions on Power Electronics., Vol. 16, N0. 3, May. 2001, pp. 390-399.
[6] L. Xu and P. Cartwright, Direct Active and Reactive Power Control of DFIG for Wind Energy Generation, IEEE Transactions on Energy Conversion., Vol. 21, N0. 3, Sept. 2006, pp. 750-758.
[7] D. Zhi and L. Xu, Direct power control od DFIG with constant switching frequency and improved transient performance, IEEE Transactions Energy Conversion, Vol. 22, N0. 1, Mar. 2007, pp. 110-118.
[8] R. V. Jacomini, A. França, E. Bim. Simulation and Experimental Studies on Double-fed Induction Generator Power Control Operating at Subsynchronous Operation Speed, The Eighth International Conference on Power Electronics and Drive Systems, November 2-5, 2009, Taipei, Taiwan, R.O.C.
[9] A. Petersson, L. Harnefors, and T. Thiringer, Evaluation of Current Control Methods for Wind Turbines Using Doubly-Fed Induction Machines, IEEE Transactions on Power Electronics., Vol. 20, N0. 1, Jan. 2005, pp. 2270-2281.
[10] I. Takahashi and T. Noguchi, A New Quick-Response and High- Efficiency Control Strategy of an Induction Motor, IEEE Transactions Industry Applications, Vol. 22, N0. 5, 1986, pp. 820-827.
[11] Z.P. Grabowski, M.P. Kazmierkowski, B.K. Bose, and F. Blaabjerg, A Simple Direct-Torque Neuro-Fuzzy Control of PWMInverter- Fed Induction Motor Drive, IEEE Transactions on Industrial Eletronics, Vol. 47, N0. 4, Aug. 2000, pp. 863-870.
[12] R.S. Rebeiro and M.N.Uddin,Performance Analysis of an FLCBased Online Adaptation of Both Hysteresis and PI Controllers for IPMSM Drive, IEEE Transactions on Industry Applications, vol.48, no.1, pp.12-19, Jan.-Feb. 2012
[13] R.S. Rebeiro and M.N.Uddin, Online Efficiency Optimization of a Fuzzy-Logic-Controller-Based IPMSM Drive, IEEE Transactions on Industry Applications, vol.47, no.2, pp.1043-1050, March-April 2011
[14] H.M. Jabr and N. C. Kar, Neuro-Fuzzy Vector Control for Doubly-Fed Wind Driven Induction Generator, IEEE Canada Electrical Power Conference, 2007, pp. 236-241.
[15] H.M. Jabr, L. Dongyun, and N.C. Kar, Experimental verification of neuro-fuzzy vector control for wind driven DFIG, Conference on IEEE Industrial Electronics Society, 2010, pp. 3073-3078.
[16] H.M. Jabr, L. Dongyun, and N.C. Kar, Design and Implementation of Neuro-Fuzzy Vector Control for Wind-Driven Doubly-Fed Induction Generator, IEEE Transactions on Sustainable Energy, vol.2, no.4, pp.404-413, 2011.
[17] R.V. Jacomini and E. Bim, Direct power control of a doubly fed induction generator by using a neuro-fuzzy controller, Power Electronics Conference (COBEP), 2011 Brazilian, pp. 32-37, 11-15 Sept. 2011.
[18] Y.S. Lai and J.C. Lin, New Hybrid Fuzzy Controller for Direct Torque Control Induction Motor Drive, IEEE Transactions on Power Eletronics, Vol. 18, N0. 5, Sept. 2003, pp. 1211-1219.
[19] R. Toufouti, S. Meziane, and H. Benalla, Direct Torque Control for Induction Motor Using Intelligent Techniques., Journal of Theoretical and Applied Information Technology, 2007, pp. 35-44.
[20] S.X. Liu, M.Y. Wang, Y.G. Chen, and S. Li, A Novel Fuzzy Direct Torque Control System for Three-Level Inverter-Fed Induction Machine, International Journal of Automation and Computing, February 2010, pp. 78-85.
[21] E. Bim, Electrical Machines and Drives, Elsevier Publications, 2009.
[22] J.S.R. Jang, ANFIS: Adaptative-network-based fuzzy inference system, IEEE Transactions on Systems, Man, and Cybernetics, Vol. 23, N0. 3, May/June 1993, pp. 665-684.
[23] T. Takagi and M. Sugeno, Fuzzy Identification of Systems and its Applications to Modeling and Control, IEEE Transactions on Systems, Man, and Cybernetics, 1985.
[24] D. Driankov, H. Hellendoorn, and M. Reinfrank, An Introduction to Fuzzy Control, Springer, 2nd., 1996.
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