Speed-sensorless control of induction motor drive using MRAS-neural self-tuning IP obsrever

• Autorzy: Chekroun S. , Zerikat M. , Benharir N.

Identyfikatory

DOI

10.15199/48.2018.12.04

Warianty tytułu

PL

Bezczujnikowe sterowanie napędem indukcyjnym przy wykorzystaniu sieci neuronowej MRAS

• Języki publikacji: EN

Abstrakty

EN

A speed-sensorless control of induction motor drive based MRAS-Neural Self-Tuning IP Observer is proposed. A Model Reference Adaptive Systems speed observer can give good rotor speed estimation, but speed errors will occur during low speed. In this work the rotor speed is estimated using MRAS-Neural Self-Tuning IP obsrever. The simulation results illustrate the good performance and the validity of the proposed observer scheme for practical applications.

PL

W artykule opisano bezczujnikowe sterowanie napędem indukcyjnym bazujące na somostrojacym się oserwatorze wykorzystującym sieć neuronową MRAS. Zazwyczaj przy małych prędkościach wirnika pojawia się błąd pomiaru prędkości. W proponowanej metodzie udaje się ten błąd wyeliminować.

Słowa kluczowe

EN

induction motor; sensorless; Model Reference Adaptive System (MRAS); neural self-tuning IP observer

PL

sterowanie bezczujnikowe napędem indukcyjnym; system adaptacyjny; MRAS; sieć neuronowa

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2018
• Tom: R. 94, nr 12
• Strony: 14--17
• Opis fizyczny: Bibliogr. 13 poz., rys., tab.

Twórcy

autor

Chekroun S.

• Department of Electrical Engineering, University Mustapha Stambouli of Mascara, Algeria,BP 305, route de Mamounia 29000, Mascara, Algeria

autor

Zerikat M.

• Department of Electrical Engineering, Polytechnic National School of Oran, Algeria, BP 1523, ElMnaouar, 31000, Oran, Algeria

autor

Benharir N.

• Department of Electrical Engineering, Polytechnic National School of Oran, Algeria, BP 1523, ElMnaouar, 31000, Oran, Algeria

Bibliografia

• [1] Dabbeti1 S., Lakshmi K.V., Sensorless speed control of an induction motor drive using predictive current and torque controllers, Advance in Electronic and Electric Engineering, (2013), Vol. 3, 1177-1196
• [2] Bullo D., Ferrara A., Rubagotti M., Sliding mode observers for sensorless control of current-fed induction motors, American Control Conference on O'Farrell Street, San Francisco, CA, USA, June 29 - July 01, (2011).
• [3] Kojabadi H.M., Farouji S.A., Zarei M., A Comparative study of various MRAS-Based IM's rotor resistance adaptation methods, Iranian Journal of Electrical and Computer Engineering, vol. 11, Winter-Spring, (2012)
• [4] Abbou A., Mahmoudi H., Performance of a sensorless speed sontrol for induction motor using DTFC strategy and intelligent techniques, Journal of Electrical Systems, (2009), Vol. 6, 64-81
• [5] Zerikat M., Bendjebbar M., Benouzza N., Dynamic fuzzyneural network controller for induction motor drive, World Academy of Science Engineering and Technology; (2005), Vol. 10, 278-283
• [6] Moaveni B., Khorshidi M., Robust speed controller design for induction motors based on IFOC and Kharitonov theorem, Turkish Journal of Electrical Engineering & Computer Sciences, Vol. 23, (2015),1173-1186
• [7] Nisha G.K., Lakaparampil Z.V., Ushakumari S., Effect of Leakage Inductance on Torque Capability of Field Oriented Controlled Induction Machine in Field Weakening Region, International Conference on Advances in Engineering and Technology, Singapore, (2014)
• [8] Kamal B.C., Suryakalavathj M., Estimation of rotor flux using neural network observer in speed sensorless induction motor drive, International Journal of Computer Applications, Vol. 79, (2013), 1-6
• [9] Greivulis J., Levchenkov A., Gorobetz M., Modelling of artificial neural network controller for electric drive with linear torque load function, Engineering for Rural Development, Jelgava. (2008), 81-87
• [10] Moinak P., Abhishek C., Sibamay D., Speed estimation of three phase induction motor using artificial neural network, International Journal of Energy and Power Engineering, Vol. 3, (2014), 52-56
• [11] Guedidi S., Zouzou S.E., Laala W., Sahraoui M., Yahia K., Broken Bar Fault Diagnosis of Induction using MCSA and neural network, CSI. In: IEEE 2011 Symposium on Diagnostics for Electrical Machines Motors Using MCSA and Neural Network, Power Electronics & Drives Conference, Italy (2011), 632 – 637
• [12] Pyne M., Chatterjee A., Dasgupta S., Speed estimation of three phase induction motor using artificial neural network, International Journal of Energy and Power Engineering, (2014), Vol. 3(2),52-56
• [13] Chekroun S., Zerikat M., Mechernene A., Benharir N., Novel Observer Scheme of Fuzzy-MRAS Sensorless Speed Control of Induction Motor Drive, IOP Conf. Series: Journal of Physics: Conf. Series,(2017)

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).