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New direct torque control of dual star induction motor using Grey Wolf optimization technique

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PL
Nowa bezpośrednia kontrola momentu obrotowego silnika indukcyjnego z podwójną gwiazdą przy użyciu techniki optymalizacji Gray Wolf
Języki publikacji
EN
Abstrakty
EN
This document shows a comparative study between two approaches for the direct torque control of the dual star induction motor drive (DSIM), the first is based on conventional PID, the second uses new heuristic optimization technique based on the grey wolf optimizer GWO-PID. The benefits of this combination can reduce the Dual SIM speed control loop problems. The GWO algorithm has been programmed and implemented in MATLAB. In addition, the most importance appropriate GWO-PID scheme combines simultaneously many index such as reducing high torque ripple, steady-state error is reduced, response time is improved and disturbances do not change the drive performance.
PL
Ten dokument przedstawia badanie porównawcze między dwoma podejściami do bezpośredniego sterowania momentem napędowym silnika indukcyjnego z podwójną gwiazdą (DSIM), pierwsze oparte jest na konwencjonalnym PID, drugie wykorzystuje nową heurystyczną technikę optymalizacji opartą na optymalizatorze szarego wilka GWO-PID. Korzyści z tej kombinacji mogą zmniejszyć problemy z pętlą kontroli prędkości Dual SIM. Algorytm GWO został zaprogramowany i zaimplementowany w MATLAB-ie. Ponadto zaproponowano i zbadano najbardziej odpowiedni schemat GWO-PID łączący jednocześnie wiele wskaźników, takich jak zmniejszenie tętnienia wysokiego momentu obrotowego, zmniejszenie błędu stanu ustalonego, poprawa czasu narastania i brak zmian w działaniu napędu.
Rocznik
Strony
109--113
Opis fizyczny
Bibliogr. 32 poz., rys., tab.
Twórcy
  • M’sila University 28000 Algeria
  • M’sila University 28000 Algeria
  • M’sila University 28000 Algeria
Bibliografia
  • [1]. Zhao Y, Lipo T.A (1995), Space vector PWM control of dual three-phase induction machine using vector space decomposition, IEEE Trans. Ind. Appl 31(5): 1100–1108.
  • [2] Hadiouche D, Razik H, Rezgzou A (2004) On the modeling and design of dual-stator windings to minimize circulating harmonic currents for VSI fed AC machines, IEEE Trans. on Industry Applications40(2): 506–515.
  • [3] Singh G.K (2002) Multi-phase induction machine drive research a survey, Electr. Power Sys. Res 61(2):139– 147.
  • [4]. Che H.S, Levi E, Jones M, Duran M.J, Hew W.P, Rahim N.A (2015), Operation of six-phase induction machine using series connected machine-side converters, IEEE Trans. Ind. Electron 61(4):164–176.
  • [5] Basak S, Chakraborty C (2015) Dual stator winding induction machine, Problems, Progress, and Future Scope, IEEE Trans. Ind. Electron 62(7):4641–4652
  • [6]. Pieńkowski K (2012) Analysis and control of dual stator winding induction motor, Archives of Electrical Engineering 61(3):421- 438
  • [7]. Takahashi I, Noguchi T(1986) A new quick-response and high-efficiency control strategy of an induction motor, IEEE Transactions on Industry Applications 22(5):820–827
  • [8]. Salima L, Tahar B, Youcef S (2013) Direct torque control of dual star induction motor, International Journal of Renewable Energy Research 3(1):333-350
  • [9]. Laamayad T, Naceri F, Abdessemed R, S. Belkacem(2013) A fuzzy sliding mode strategy for control of the dual star induction machine, Journal of Electrical Engineering 13(3):203–216
  • [10]. Bouziane M, Abdelkader M (2014) A neural network based speed control of a dual star induction motor, International Journal of Electrical and Computer Engineering 4(6):952–961
  • [11]. Premkumar K, Manikandan B (2015) Speed control of brushless DC motor using bat algorithm optimized adaptive neuro-fuzzy inference system, Applied Soft Computing 32(3):403–419
  • [12]. Laamayad T, Belkacem S (2015) The stable algorithm based on a model reference adaptive control for the dual star induction machine drives, Journal of Electrical Engineering 15(4):52–63
  • [13]. Azib, D. Ziane, T. Rekioua, A. Tounzi (2016) Robustness of the direct torque control of double star induction motor in fault condition, Rev. Roum. Sci.Techn. Électrotechn. et Énergn61(2) :147–152
  • [14].Tabbache B, Douida S , Benbouzid M , Diallo D, Kheloui A, (2017) Direct torque control of five-leg inverter-dual induction motor powertrain for electric vehicles, Electrical Engineering 99(3): 1073–1085
  • [15]. Taheri A (2016) Harmonic reduction of direct torque control of six-phase induction motor, ISA Transactions 63(4): 299–314
  • [16]. Merabet E, Amimeur H, Hamoudi F, Abdessemed R, Self tuning (2011) fuzzy logic Controller for a dual star induction machine. Journal of Electr Eng Technol 6(4): 33–54
  • [17]. Farah N, Talib M.H.N, Ibrahim Z, Azri M, Rasin Z (2017) Self-tuned output scaling factor of fuzzy logic speed control of induction motor drive, 7th IEEE International Conference on System Engineering and Technology, 2–3 October Malaysia, pp 612–620
  • [18]. Garg H, (2015) A hybrid GA - GSA algorithm for optimizing the performance of an industrial system by utilizing uncertain data, Handb. Res. Artif. Intell. Tech. Algorithm. IGI Global ,pp 620– 654
  • [19]. Zemmit A, Messalti S, Harrag A (2017) A new improved DTC of doubly fed induction machine using GA-based PI controller. Ain Shams Engineering Journal8(4): 481–706
  • [20]. Garg H, (2016) A hybrid PSO-GA algorithm for constrained optimization problems, Applied Mathematics and Computation 274(1): 1292–1305
  • [21]. Ranjani M , Murugesan P, Optimal fuzzy controller parameters using PSO for speed control of Quasi-Z Source DC/DC converter fed drive, Applied Soft Computing 27 (2015) 332–356
  • [22]. Abd-El-Waheda W.F, El-Shorbagy M.A. (2011) Integrating particle swarm optimization with genetic algorithms for solving nonlinear optimization problems, Journal of Computational and Applied Mathematics 235(4):1446–1453
  • [23]. Goldberg D.E, (1989) Genetic Algorithm in Search, Optimization and Machine Learning, MA: Addison-Wesley
  • [24]. Bharti O.P, Saket R.K, Nagar S.K(2017) Controller design for doubly fed induction generator using particle swarm optimization technique, Renewable Energy 114(3):1394-1406
  • [25]. Allaoua B, Gasbaoui B, Mebarki B (2009) Setting up PID DC motor speed control alteration parameters using particle swarm optimization strategy ,Leonardo Electronic Journal of Practices and Technologies 14(2) :19-32
  • [26]. Bouallegue S, Haggege, Ayadi J, Benrejeb M, A (2012), PID-type fuzzy logic controller tuning based on particle swarm optimization, Engineering Applications of Artificial Intelligence 25(3): 484–493
  • [27]. S. Mirjalili, S. M. Mirjalili, and A. Lewis, (2014) “Grey wolf optimizer,” Advances in Engineering Software, 69: 46–61.
  • [28] G. M. Komaki and V. Kayvanfar, (2015) “Grey wolf optimizer algorithm for the two-stage assembly flow shop scheduling problem with release time,” Journal of Computational Science, 8: 109–120.
  • [29] Y. Sharma and L. C. Saikia, (2015) “Automatic generation control of a multi-area ST-thermal power system using grey wolf optimizer algorithm based classical controllers,” International Journal of Electrical Power & Energy Systems, vol. 73, pp. 853–862.
  • [30] S. A. Medjahed, T. A. Saadi, A. Benyetto, and M. Ouali, (2016)“Gray wolf optimizer for hyperspectral band selection,” Applied Soft Computing, vol. 40, pp. 178–186.
  • [31] E. Emary, H. M. Zawbaa, and A. E. Hassanien, (2016) “Binary grey wolf optimization approaches for feature selection,” Neurocomputing, vol. 172, pp. 371–381.
  • [32] R. E. Precup, R. C. David, E. M. Petriu, A. I. Szedlak-Stinean, and C. A. Bojan-Dragos, (2016) “Grey wolf optimizer-based approach to the tuning of pi-fuzzy controllers with a reduced process parametric sensitivity,” IFAC-PapersOnLine, vol. 49, no. 5, pp. 55–60.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki i promocja sportu (2025).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e09aba11-2c60-4be2-8bbc-9ef4e0b0e7bf
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