Warianty tytułu
Sterowanie prędkością silników z przełączaną reluktancją za pomocą zoptymalizowanego regulatora PID
Języki publikacji
Abstrakty
The switched reluctance motor (SRM) has turned out to be an outstanding resolution for a various appliances. The modern invents of SRM grant consumers to yield advantage of small starting currents , better efficiency and robust structure that illustrates this kind of motor. This article aims at analyzing and modeling the switched reluctance motor speed controller utilizing a Proportional Integral derivative (PID) controller. The non-linear character of the SRM magnetic properties is currently fetched into attention for modeling . These nonlinearities of the switched reluctance machines attain the traditional PID controller an inadequate selection for appliance where high dynamic performance drive is required. Genetic Algorithm (GA) is manipulated to adjust the PID coefficients for the SRM drive. The consequences achieved indicates that the utilization of these established algorithms controller enhances the transient and steady state performances.
Silnik z przełączaną reluktancją (SRM) okazał się być znakomitym rozwiązaniem dla różnych urządzeń. Nowoczesne wynalazki SRM dają konsumentom korzyści w postaci małych prądów rozruchowych, lepszej wydajności i solidnej konstrukcji, która ilustruje ten rodzaj silnika. Celem artykułu jest analiza i modelowanie regulatora prędkości silnika z przełączaną reluktancją, wykorzystującego regulator proporcjonalnocałkująco-pochodny (PID). Obecnie zwraca się uwagę na nieliniowy charakter właściwości magnetycznych SRM. Te nieliniowości przełączanych maszyn reluktancyjnych powodują, że tradycyjny regulator PID jest nieodpowiednim wyborem dla urządzeń, w których wymagana jest wysoka dynamika napędu. Algorytm genetyczny (GA) jest manipulowany w celu dostosowania współczynników PID dla napędu SRM. Uzyskane konsekwencje wskazują, że wykorzystanie tych ustalonych algorytmów kontrolera poprawia wydajność w stanie nieustalonym i ustalonym.
Czasopismo
Rocznik
Tom
Strony
46--50
Opis fizyczny
Bibliogr. 22 poz., rys.
Twórcy
autor
- Ninevah University, Iraq, muhammed.ibrahim@uoninevah.edu.iq
- University of Mosul, Iraq
- University of Mosul, Iraq, ahmed_alsammak@uomosul.edu.iq
Bibliografia
- [1] Le-Huy, Hoang, and Patrice Brunelle. "A versatile nonlinearswitched reluctance motor model in Simulink using realistic andanalytical magnetization characteristics." 31st Annual Conference of IEEE Industrial Electronics Society, 2005. IECON 2005.. IEEE, 2005.
- [2] Qawaqzeh, Mohamed Zaidan, et al. "Determination of power parameters of switched reluctance motor based on instantaneous values of phase voltages and currents." Przegląd Elektrotechniczny 1.12 (2016): 103-106.
- [3] Bilgin, Berker, James Weisheng Jiang, and Ali Emadi. "Switched reluctance motor drives: fundamentals to applications." Boca Raton, FL (2018).
- [4] Correia, Wilkley Bezerra, et al. "The t-polynomial approach for lqg control applied to a switched reluctance motor (srm)." Przeglad Elektrotechniczny 1.2 (2016): 163169.
- [5] Krishnan, Ramu. Switched reluctance motor drives: modeling, simulation, analysis, design, and applications. CRC press, 2017.
- [6] Song, Shoujun, and Weiguo Liu. "Fuzzy parameters self-tuning PID control of switched reluctance motor based on Simulink/NCD." 2006 International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (CIMCA'06). IEEE, 2006.
- [7] Xia, Changliang, Ziran Chen, and Mei Xue. "Adaptive PWM speed control for switched reluctance motors based on RBF neural network." 2006 6th World Congress on Intelligent Control and Automation. Vol. 2. IEEE, 2006.
- [8] Liu, Weiguo, and Shoujun Song. "Application of fuzzy control in switched reluctance motor speed regulating system." 2006 International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (CIMCA'06). IEEE, 2006.
- [9] Joseph, X. Felix, and S. Pushpa Kumar. "Design and simulation of a PI controlled soft switched front end converterfor switched reluctance motor." International Journal of Computer Applications 34.10 (2011): 9-15.
- [10] Evangeline, S. Jebarani, K. Venmathi, and S. Ajayan. "Speed control of switched reluctance motor using fractional order control." 2017 International Conference on Innovations in Electrical, Electronics, Instrumentation and Media Technology (ICEEIMT). IEEE, 2017.
- [11] Indragandhi, V., R. Selvamathi, and T. Arunkumari. "Speed control of a switched reluctance motor using PID controller forPV based water pumping applications." 2017 Innovations in Power and Advanced Computing Technologies (i-PACT). IEEE, 2017.
- [12] Li, Cunhe, et al. "Robust adaptive neural network control for switched reluctance motor drives." Automatika: časopis za automatiku, mjerenje, elektroniku, računarstvo i komunikacije 59.1 (2018): 24-34.
- [13] Sridharan, S., and S. Sudha. "Optimisation of speed control for switched reluctance motor using matrix converter." International Journal of Computer Aided Engineering and Technology 11.2 (2019): 253-266.
- [14] Sovicka, Pavel, Pavol Rafajdus, and Vladimir Vavrus. "Switched reluctance motor drive with low-speed performance improvement." Electrical Engineering 102.1 (2020): 27-41.
- [15] Souza, Darielson A., et al. "Optimal lqi and pid synthesis for speed control of switched reluctance motor using metaheuristic techniques." International Journal of Control, Automation and Systems 19.1 (2021): 221-229.
- [16] Bilgin, Berker, James Weisheng Jiang, and Ali Emadi. "Switched reluctance motor drives: fundamentals to applications." Boca Raton, FL (2018).
- [17] Cajander, David, and Hoang Le-Huy. "Design and optimization of a torque controller for a switched reluctance motor drive for electric vehicles by simulation." Mathematics and computers in simulation 71.4-6 (2006): 333-344.
- [18] Torrey, D. A., X-M. Niu, and E. J. Unkauf. "Analytical modelling of variable-reluctance machine magnetisation characteristics." IEE Proceedings-Electric Power Applications 142.1 (1995): 14-22.
- [19] Khather, Salam Ibrahim, and Muhammed A. Ibrahim. "Modelingand simulation of SEPIC controlled converter using PID controller." International Journal of Power Electronics and Drive Systems 11.2 (2020): 833.
- [20] Karkar, Nora, et al. "Control of PID parameters by iterative learning based on neural network." Przegląd Elektrotechniczny 97 (2021).
- [21] Ibrahim, Muhammed Abduljaleel. "Performance evaluation of PI controller for positive output Luo converter." International Journal of Power Electronics and Drive Systems 11.4 (2020): 1816.
- [22] Ibrahim, Muhammed A., Ausama Kh Mahmood, and Nashwan Saleh Sultan. "Optimal PID controller of a brushless DC motor using genetic algorithm." Int J Pow Elec & Dri Syst ISSN 2088.8694 (2019): 8694.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.baztech-3230f079-996e-46e4-84c3-c0ef54973ff9