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Tytuł artykułu

Speed Sensorless Control of Induction Motor Based on a Non-Linear Flux and Speed Observer with Parameters Estimation and Considering Iron Loss

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
PL
Sterowanie maszyną indukcyjną z bezczujnikowym pomiarem prędkości obrotowej – nieliniowy obserwator strumienia i prędkości z estymacją parametrów i uwzględnieniem strat w żelazie
Języki publikacji
EN
Abstrakty
EN
In this paper, a control method is presented for induction motor which offers high efficiency and high dynamics even considering the influences of iron loss. Recently, research to consider the influences of iron loss has been made in the vector control of an induction motor. Vector control method is a quite complex task which demands precise information about the rotor speed and the position of the magnetic flux. The vector control method presented in this paper, estimates both rotor speed and amplitude magnetic flux rotor. However, there are also applications in which even speed sensors should be omitted. In this method, three-phase motor currents and DC link voltage are measured by means of a nonlinear observer and considering the Lyapunov function for current error, motor parameters, rotor shaft and position of flux are estimated. To stabilize the control system, the Lyapunov function for error, is used. Then, using the genetic algorithm, the value of controlling coefficients their and general effects on system's behavior are obtained. The simulation and experimental results confirm the resistant performance and the proper dynamic efficiency of this method.
PL
W artykule przedstawiono algorytm sterowania maszyną indukcyjną, uwzględniający straty w żelazie. Sterowanie opiera się na bezczujnikowym pomiarze prędkości obrotowej, przy pomocy obserwatora. Korzystając z pomiarów prądów fazowych i napięcia DC-link, z funkcji Lyapunov’a wyznaczana jest prędkość i strumień wirnika. Implementacja algorytmu genetycznego pozwoliła na ocenę wpływu współczynników regulacji na odpowiedź układu. Przedstawiono wyniki symulacyjne i eksperymentalne.
Rocznik
Strony
89--97
Opis fizyczny
Bibliogr. 23 poz., schem., tab., wykr.
Twórcy
  • Iran University of Science and Technology (IUST)
  • Iran University of Science and Technology (IUST)
Bibliografia
  • [1] Kouki Matsuse, Shotaro Taniguchi, Tatsuya Yoshizumi, and Kazushige Namiki,” A Speed-Sensorless Vector Control of Induction Motor Operating at High Efficiency Taking Core Loss into Account”, IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 37, NO. 2, MARCH/APRIL 2001.
  • [2] Jia-jun WANG, Jie HE, “Torque and flux direct backstepping control of induction motor”, the 7th World Congress on Intelligent Control and Automation June 25 - 27, 2008, Chongqing, China.
  • [3] Epaminondas D. Mitronikas and Athanasios N. Safacas, Member, IEEE,” An Improved Sensorless Vector-Control Method for an Induction Motor Drive”, IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 52, NO. 6, DECEMBER 2005.
  • [4] Epaminondas D. Mitronikas and Athanasios N. Safacas, Member, IEEE, “An Improved Sensorless Vector-Control Method for an Induction Motor Drive,” IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 52, NO. 6, DECEMBER 2005.
  • [5] J. Holtz and Q. Juntao, “Sensorless vector control of induction motors at very low speed using a nonlinear inverter model and parameter identification,” IEEE Trans. Ind. Appl., vol. 38, no. 4, pp. 1087–1095, Jul./Aug. 2002.
  • [6] Maurizio Cirrincione, Marcello Pucci, Giansalvo Cirrincione, and Gérard-André Capolino, “Constrained Minimization for Parameter Estimation of Induction Motors in Saturated and Unsaturated Conditions,” IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 52, NO. 5, OCTOBER 2005.
  • [7] Marcello Montanari, Sergei M. Peresada, Carlo Rossi, and Andrea Tilli, “Speed Sensorless Control of Induction Motors Based on a Reduced-Order Adaptive Observer,” IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, VOL. 15, NO. 6, NOVEMBER 2007
  • [8] C. Shauder, “Adaptive speed identification for vector control of induction motors without rotational transducers,” IEEE Trans. Ind. Appl., vol. 28, no. 5, pp. 1054–1061, Sep./Oct. 1992.
  • [9] C. Lascu, I. Boldea, and F. Blaabjerg, “A modified direct torque control for induction motor sensorless drive,” IEEE Trans. Ind. Appl., vol. 36,no. 1, pp. 122–130, Jan./Feb. 2000.
  • [10] H. Kubota, I. Sato, Y. Tamura, K. Matsuse, H. Ohta, and Y. Hori, “Stable operation of adaptive observer based sensorless induction motor drives in regenerating mode at low speeds,” in Conf. Rec. IEEE-IAS Annu.Meeting, vol. 1, Oct. 2001, pp. 469–474.
  • [11] G. Guidi and H. Umida, “A novel stator resistance estimation method for speed-sensorless induction motor drives,” IEEE Trans. Ind. Appl., vol. 36, no. 6, pp. 1619–1627, Nov./Dec. 2000.
  • [12] H. Kubota, I. Sato, Y. Tamura, H. Ohta, and Y. Hori, “Stable operation of adaptive observer based sensorless induction motor drives in regenerating mode at low speeds,” IEEE Trans. Ind. Appl., vol. 38, no. 4, pp. 1081–1086, Jul./Aug. 2002.
  • [13] H. Sugimoto, “One improving measures of stability in regeneration operation of speed sensorless vector control induction motor system using adaptive observer of secondary magnetic flux,” in Proc. Int. Power Electronics Conf. (IPEC), Tokyo, Japan, 2000, vol. 3, pp. 1069–1074.
  • [14] H. Tajima, G. Guidi, and H. Umida, “Consideration about problems and solutions of speed estimation method and parameter tuning for speedsensorless vector control of induction motor drives,” IEEE Trans. Ind. Appl., vol. 38, no. 5, pp. 1282–1289, Sep./Oct. 2002.
  • [15] Surapong Suwankawin and Somboon Sangwongwanich, “Design Strategy of an Adaptive Full-Order Observer for Speed-Sensorless Induction-Motor Drives—Tracking Performance and Stabilization”, IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 53, NO. 1, FEBRUARY 2006.
  • [16] K. Shi, T. Chan, Y. Wong, and S. Ho, “Speed estimation of an induction motor drive using an optimized extended Kalman filter,” IEEE Trans. Ind. Electron., vol. 49, no. 1, pp. 124–133, Feb. 2002.
  • [17] B. Peterson, “Induction machine speed estimation, observations on observers,” Ph.D. dissertation, Dept. Ind. Elect. Eng. Autom., Lund Inst. Technol., Lund, Sweden, 1996.
  • [18] H. Kubota, K. Matsuse, and T. Nakano, “DSP-based speed adaptive flux observer of induction motor,” IEEE Trans. Ind. Appl., vol. 29, no. 2, pp. 344–348, Mar./Apr. 1993.
  • [19] Pavel Vaclavek, and Petr Blaha, Lyapunov-Function-Based Flux and Speed Observerfor AC Induction Motor Sensorless Control and Parameters Estimation,” IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 53, NO. 1, FEBRUARY 2006.
  • [20] Giovanni Bottiglieri, Student Alfio Consoli, and Thomas A. Lipo, Life” Modeling of Saturated Induction Machines With Injected High-Frequency Signals,” IEEE TRANSACTIONS ON ENERGY CONVERSION, VOL. 22, NO. 4, DECEMBER 2007.
  • [21] Faa-Jeng Lin, Senior Member, IEEE, Rong-Jong Wai, Member, IEEE, Wen-Der Chou, and Shu-Peng Hsu,” Adaptive Backstepping Control Using Recurrent Neural Network for Linear Induction Motor Drive”, IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 49, NO. 1, FEBRUARY 2002
  • [22] J.-W. Kim and S. W. Kim, “A novel parametric identification method using dynamic encoding algorithm for searches (DEAS),” in Proc. Int.Conf. Control, Automation and Systems, Oct. 2002, pp. 406–411.
  • [23] K. L. Shi, T. F. Chan, Y. K. Wong, and S. L. Ho, “Speed estimation of induction motor using extended Kalman filter,” in Proc. IEEE WinterMeeting 2000, vol. 1, Singapore, Jan. 23–27, 2000, pp. 243–248.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b1e8d877-ca86-4715-abe0-a5950848654b
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