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Control input limited switched reluctance motor with auxiliary sliding mode position tracking control

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The drive system of a switched reluctance motor (SRM) is a nonlinear one with coupling between the rotor position, inductance, and flux linkage. Moreover, the system parameters change with the external environment such as temperature, humidity, and pressure. At the same time, uncertain factors including friction, torque fluctuation, and external interference in the system, reduce system stability and reliability. To effectively improve the influence of uncertain factors on the performance of an SRM system, this study proposes an auxiliary sliding position tracking method, under the condition of limited control input. First, the mathematical model of the system was established according to the structure and characteristics of an SRM.Second, an auxiliary sliding mode position tracking controller was designed by constructing the auxiliary system and utilizing the sliding mode control theory. Finally, the effectiveness and superiority of the proposed method were verified through comparison with proportional integral differential (PID) control and the traditional sliding mode control using simulation. Results demonstrate that under limited control input, the auxiliary sliding position tracking control method still delivers rapid and error-free tracking of the position and speed for the change of model parameters. The recommended scheme has a response time 2.9 times shorter than that of PID control. Furthermore,the steady-state errors of the PID control position and speed are 0.66 rad and 1.62 rad/s, respectively. The control input of the traditional sliding mode control has greater chattering than the proposed method. When the system has interference, the designed method under the condition of limited control in-put can achieve the desired tracking command within 1.7 s. The steady-state error is 0.0044 rad, and the steady-state accuracy of the developed scheme is 10.3 times higher than that of PID control. Therefore, the proposed method enjoys both high position tracking accuracy and strong robustness to external disturbances.
Rocznik
Strony
341--350
Opis fizyczny
Bibliogr. 23 poz., rys., wykr.
Twórcy
  • Nanyang Institute of Technology, Henan Province, 473004, China
autor
  • Nanyang explosion proof Electrical Research Institute, Henan Province, 473004, China
autor
  • Henan Institute of Technology, Henan Province, 453000, China
autor
  • Department of Informatics, University of Zurich, Zurich, 8050, Switzerland
Bibliografia
  • [1] Y. Li, Q. Ma, and P. Xu. Improved general modelling method of SRMs based on normalised flux linkage. Institution of Engineering and Technology Electric Power Applications, 14 (2): 316-324, 2020.
  • [2] B. Howey, B. Bilgin, and A. Emadi. Design of a mutually coupled external rotor direct drive E-bike switched reluctance motor. Institution of Engineering and Technology Electrical Systemsin Transportation, 10 (1): 89-95, 2020.
  • [3] S. Li, S. Zhang, T. Habetler, and R. Harley. Modeling, design optimization, and applications of switched reluctance machines - a review. IEEE Transactions on Industry Applications, 55 (3): 2660-2681, 2019.
  • [4] E. Bostanci, M. Moallem, A. Parsapour, and B. Fahimi. Opportunities and challenges of switched reluctance motor drives for electric propulsion: a comparative study. IEEE Transactions on Transportation Electrification, 3 (1): 58-75, 2017.
  • [5] B. Burkhart,A. Klein-Hessling, I. Ralev, C. Weiss, and D. R. De. Technology, research and applications of switched reluctance drives. CPSS Transactions on Power Electronics and Applications, 2 (1): 12-27, 2017.
  • [6] S. G. Zuo, M. T. Liu, and S. L. Hu. Analytical modeling for inductance and torque of switched reluctance motor considering iron core magnetic saturation. Journal of Xi’an Jiaotong University, 53 (7): 118-125, 143, 2019.
  • [7] S. G. Zuo, Y. P. Zheng, S. L. Hu, and Y. Mao. Analytical modeling of radial electromagnetic force for switched reluctance motor considering saturation effect. Journal of Tongji University (Natural Science), 46 (12): 1736-1744, 2018.
  • [8] W. Ye, Q.W. Ma, P. Xu, and P.M. Zhang. Non-linear fitting method for torque-angle characteristic model of switched reluctance motor. Journal of Beijing University of Aeronautics and Astronautics, 45 (1): 83-92, 2019.
  • [9] H. Jeon, J. Lee, S. Han, J. H. Kim, C. J. Hyeon, H. M. Kim, H. Kang, T. K. Ko, and Y. S. Yoon. PID control of an electromagnet-based rotary HTS flux pump for maintaining constant fieldin HTS synchronous motors. IEEE Transactionson Applied Superconductivity, 28 (4): 1-5, 2018.
  • [10] L. Angel and J. Viola. Design and statistical robustness analysis of FOPID, IOPID and SIMCPID controllers applied to a motor-generator system. IEEE Latin America Transactions,13 (12): 3724-3734, 2015.
  • [11] Y. He, Y. Tang, D. Lee, and J. Ahn. Suspending control scheme of 8/10 bearingless SRM based on adaptive fuzzy PID controller. Chinese Journal of Electrical Engineering, 2 (2): 60-67, 2016.
  • [12] A. Nguyen, M. Rafaq, H. Choi, and J. Jung. A model reference adaptive control based speed controller for a surface - mounted permanent magnet synchronous motor drive. IEEE Transactions on Industrial Electronics, 65 (2): 9399-9409, 2018.
  • [13] C. Tang, Y. Dai, and Y. Xiao. High precision position control of PMSLM using adaptive sliding-mode approach. Journal of Electrical Systems,10 (4): 456-464, 2014.
  • [14] A. Nihad, U. Ateeq, A. Waqar, and M. Hamid. Disturbance observer based robust sliding mode control of permanent magnet synchronous motor. Journal of Electrical Engineering and Technology, 14 (6): 2531-2538, 2019.
  • [15] K. Ali, T. Hamed, and B. Oscar. Dynamic sliding mode position control of induction motors based load torque compensation using adaptive state observer. Compel, 37 (6): 2249-2262, 2018.
  • [16] H. Abdelkader, B. Houcine, C. Ilhami, and K. Korhan. Backstepping control of a separately excited DC motor. Electrical Engineering,100 (3): 1393-1403, 2018.
  • [17] C. Tang and Z. Duan. Direct thrust-controlled PMSLM servo system based on back-stepping control. IEEJ Transactions on Electrical and Electronic Engineering, 13 (5): 785-790, 2018.
  • [18] L. Chen, H. H. Wang, J. W. Zhang, C. Tan, and Y. Wang. Optimization design of passivity-based controller for bearingless switched reluctance motor. Journal of Guangxi University (Natural Science Edition, 43 (5): 1756-1764, 2018.
  • [19] C. Mohamed, G. Amar, T. Med, and G. Noureddine. Senseless finite-state predictive torque control of induction motor fed by four-switch inverter using extended Kalman filter. Compel, 37 (6): 2006-2024, 2018.
  • [20] S. Masoudi, M. R. Soltanpour, and H. Abdollahi. A new adaptive fuzzy control method for a linear switched reluctance motor. Institution of Engineering and Technology Electric Power Applications, 12 (9): 1328-1336, 2018.
  • [21] K. Xu, C. S. Tang, J. Yang, J. Zhang, and J. Hu. Optimization of linear switched reluctance motor for single neuron adaptive position tracking control based on fruit fly optimization algorithm. Journal of Engineering Science and Technology Review, 13 (1): 160-165, 2020.
  • [22] C. S. Tang, Z. M. Li, and C. Li. Disturbance compensation based robust sliding-mode tracking control for uncertain robots. Modular MachineTool and Automatic Manufacturing Technique, (7): 99-101, 104, 2016.
  • [23] E. L. Zhao, J. F. Yu, S. Cheng, and J. P. Yu. Observer-based fuzzy backstepping position tracking control for asynchronous motor stochastic system. Motor and Control Application, 47 (1): 8-14, 2020.
Uwagi
PL
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-88da55e2-3b3c-4b2f-a258-2c46345f1f42
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