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Performance improvement of ANFIS with sliding mode based on MRAS sensorless speed controller for induction motor drive

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
PL
Poprawa właściwości systemu ANFIS w sterowaniu silnikiem indukcyjnym w trybie ślizgowym bezczujnikowym z obserwatorem MRAS
Języki publikacji
EN
Abstrakty
EN
This paper is focused on a performance improvement of ANFIS with sliding mode based on MRAS sensorless speed controller for induction motor drive associated with the IFOC strategy. The control strategy consists of the combination of the sliding mode with the ANFIS strategy. In order to estimate the speed of the IM, MRAS sensorless strategy associated with ANFIS system is used. This controller has high accuracy, suitable performance, high robustness and high tracking efficiency. To provide a numerical comparison between different controllers, a performance index based on speed error is assigned. The obtained results show that ANFIS Controller associated with MRAS observer overcome the problem of estimation of the speed of the motor particularly at low speed. The main advantages of the proposed method are the robustness to parameter variations and load changes.
PL
W artykule analizowano możliwość poprawy systemu ANFIS ze ślizgowym bezczujnikowym sterownikiem prędkości silnika indukcyjnego. Dla porównania różnych sterowników wprowadzono indeks bazujący na błędzie prędkości. Wykazano że system ANFIS z obserwatorem MRAS rozwiązuje problem określania prędkości szczególnie przy małych prędkościach.
Rocznik
Strony
269--275
Opis fizyczny
Bibliogr. 24 poz., rys., tab.
Twórcy
  • Laboratory of Automatics and Systems Analysis (L.A.A.S.), Department of Electrical Engineering, National Polytechnic School –Maurice Audin - Oran. BP 1523 El’ M’naouer, Oran, Algeria
  • Laboratory of Automatics and Systems Analysis (L.A.A.S.), Department of Electrical Engineering, National Polytechnic School –Maurice Audin - Oran. BP 1523 El’ M’naouer, Oran, Algeria
  • Laboratory of Automatics and Systems Analysis (L.A.A.S.), Department of Electrical Engineering, National Polytechnic School –Maurice Audin - Oran. BP 1523 El’ M’naouer, Oran, Algeria
  • Department of Electrical Engineering, University Mustapha Stambouli of Mascara.BP.305, Route El Mamounia, 29000 Mascara Algeria
Bibliografia
  • [1]. Pei.W., “Lagrangian Modelling and Passivity Based Control of Induction Motors for electric vehicles", in International Federation of Automatic Control (IFAC), 2018, vol.51, no.31, pp.499-503.
  • [2]. Zheng.W., Liu.J., “Hybrid Sliding Mode ControlTechnology of Electric Vehicle Based on Wireless Sensor", in International Journal of Online and Biomedical Engineering (IJOE) ,2017, vol.13, no.5.
  • [3]. Echeikh.H.,Trabelsi.R., Iqbal.A., Mimounia. M.F., “Real Time Implementation of Indirect Rotor Flux Oriented Control of a Five-Phase Induction Motor with Novel Rotor Resistance Adaption Using Sliding Mode Observer", in Journal of The Franklin Institute, 2018, vol. 355, no.5, pp. 2112-2141. PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 95 NR 12/2019 275
  • [4]. Fereka.D.,Zerikat.M.,Belaidi.A.,"MRAS Sensorless Speed Control of an Induction Motor Drive based on Fuzzy Sliding Mode Control", in 7th International Conference on Systems and Control, Spain,2018.
  • [5]. Schauder.C., “Adaptive Speed Identification for Vector Control of Induction Motors without Rotational Transducers", in IEEE Transactions on Industry Applications,1992, vol. 28, no.5, pp.1054-1061.
  • [6]. Kumar.K.K., Sasikanth.S., Dinesh.L., “Simulation of sensorless induction motor based on model reference adaptive system (MRAS), International Journal of Engineering Research and Applications" (IJERA), 2016, vol.2, no.6, pp.255-260.
  • [7]. Kumar.A.,Ramesh.T., “Mras Speed Estimator For Speed Sensorless Ifo Of An Induction Motor Drive Using Fuzzy Logic Controller", in International Conference on Energy, Power and Environment: Towards Sustainable Growth (ICEPE), 2015.
  • [8]. Haddoun.A., Benbouzid.M.E.H., Diallo. D., Abdessemed.R., Ghouili. J., Srairi. K., “Comparative analysis of estimation techniques of SFOC induction motor for electric vehicles", in 18th International conference on electrical machines, 2008.
  • [9]. Holtz.J., “Methods for speed sensorless control of AC drives", in Proc. IEEE PCC-Yokohama, 1993, pp. 415-420.
  • [10]. Manriquez.E.Q., Sanchez. E.N., Harley. R.G.,Li.S.,Felix. R.A., “Neural Sliding Mode Control for Induction Motors Using Rapid Control Prototyping",in International Federation of Automatic Control (IFAC) Hosting by Elsevier Ltd, 2017, pp.9625-9630.
  • [11]. Bousmaha Bouchiba.B, Ismail.K.B., Fellah.M.K.,Hazzab.A., “Artificial Neural Network Sliding Mode Control For Multi- Machine Web Winding System", in Rev. Roum. Sci. Techn.- Électrotechn. et Énerg, Bucarest 2017,vol.62, no.1, pp. 109- 113.
  • [12]. Giribabu.D., Kumar.K., Chandra.S., “ANFIS Based Modified Voltage Model RFMRAS Speed Observer For Induction Motor Drive", in International Conference on Energy, Power and Environment: Towards Sustainable Growth (ICEPE), 2015.
  • [13]. Mishra.R.N.,Kanungo.R.M.,“Real time implementation of an ANFIS-based induction motor drive via feedback linearization for performance enhancement", in Engineering Science and Technology, an International Journal, 2016, vol.19, no.4, pp.1714-1730.
  • [14]. Amrane. F., Chaiba.A., “A Novel Direct Power Control for Grid-Connected Doubly Fed Induction Generator Based on Hybrid Artificial Intelligent Control with Space Vector Modulation", in Rev. Roum. Sci. Techn.- Electrotechn. et Energ, bucarest 2016, vol. 61, no.3, pp. 263-268.
  • [15]. Saghafinia.A. Ping.H.W.,Member,IEEE, Uddin. M.N., Senior Member, IEEE, and Gaied. K.S., Member, IEEE, "Adaptive Fuzzy Sliding-Mode Control into Chattering-Free IM Drive", in IEEE Transactions on Industry Applications,2015, vol.51, no.1 , pp.692-701.
  • [16]. Korondi.P., Hashimoto.H., “park vector based sliding mode control of ups with unbalanced and nonlinear load", in Periodica Polytechnica Ser. El. Eng, 1999, vol.43, no.1, pp. 65- 79.
  • [17]. Chekroune.S., Zerikat.M., Benharir.N., “Speed- Sensorless Control of Induction Motor Drive using MRASNeural Self-Tuning IP Observer" in Przegląd Elektrotechniczny, 2018, R. 94 NR 12/2018.
  • [18]. Leonhard. W., “Control of Electrical Drives", in SPRINGER, 2nd Edition, 1996.
  • [19]. Kusagur.A., Kodad.S.F., and Sankar Ram. B.V., "Modeling, Design & Simulation of an Adaptive Neuro-Fuzzy Inference System (ANFIS) for Speed Control of Induction Motor", in International Journal of Computer Applications, 2010, vol.6, no.12.
  • [20]. Bouhoune.K.,Yazid.K.,Boucherit.M.S., Chériti.A.,"Hybrid control of the three phase induction machine using artificial neural networks and fuzzy logic", in Applied Soft Computing Journal (Elsevier),2017, vol .5, pp.289-301.
  • [21]. Areed.F., Amira.G., Haikal.Y., Mohammed. R.H., “Adaptive neuro-fuzzy control of an induction motor", in Ain Shams Engineering Journal, 2010, vol.1,pp 71 -78.
  • [22]. Loganathan.C., Girija.K.V., Hybrid Learning For Adaptive Neuro Fuzzy Inference System Research Inventy: International Journal Of Engineering And Science, 2013, Vol.2,pp 06-13.
  • [23]. Ansari. A.Q., Gupta.N., Backpropagation Algorithm for Neuro- Fuzzy Integrated System with its Application National Conference on Power, Instrumentation, Energy, and Control, AMU Aligarh, February 2011.
  • [24].Chekroun.S.,Zerikat.M.,Mechernene.A.,Benharir.N “Development of a Speed Sensorless IM Drives using an Adaptive Neuro-Fuzzy Flux Observer, Journal of Electrical Engineering JEE, 2013,Vol. 13, pp 173-179.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-0acbc4c2-65c1-445e-ade7-08add6e35bd7
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