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The T-polynomial approach for LQG control applied to a Switched Reluctance Motor (SRM)

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Warianty tytułu
PL
T-wielomianowa metoda sterowania przełączalnym silnikiem reluktancyjnym
Języki publikacji
EN
Abstrakty
EN
This paper proposes a tuning procedure that combines the well known T-polynomial, from predictive control, with the LQG algorithm. The proposed scheme was successfully applied to a speed loop of a switched reluctance motor (SRM), which is known by its specific issues related to driving and control. Such characteristics make the SRM a strong set up to exploit the proposed solution. Results are compared with both the predictive controller approach GPCBC and the classical LQG/LTR, analysed regarding the transient and disturbance rejection. Power analysis of the control signal shows a power efficiency improvement favourable for the proposed approach.
PL
Opisano sposób sterowania silnikiem reluktancyjnym wykorzystująca metodę T-wielomianu z algorytmem LQG – linear quadratic Gaussian. Metodę porównano z innymi metodami jak GPCBC I LQG/LTR pod kątem tłumienia zakłóceń i stanów chwilowych.
Rocznik
Strony
161--167
Opis fizyczny
Bibliogr. rys., tab., wykr.
Twórcy
  • Computer and Electrical Engineering courses at Sobral, Universidade Federal do Ceará - Campus Mucambinho, Rua Estanislau Frota, S/N, 62000 Sobral- CE, Brazil
  • Computer and Electrical Engineering courses at Sobral, Universidade Federal do Ceará - Campus Mucambinho, Rua Estanislau Frota, S/N, 62000 Sobral- CE, Brazil
autor
  • Department of Electrical Engineering, Universidade Federal do Ceará – Campus do Pici, P.O.Box 6001 - Fortaleza-CE,Brazil
  • Department of Electrical Engineering, Universidade Federal do Ceará – Campus do Pici, P.O.Box 6001 - Fortaleza-CE,Brazil
autor
  • Computer and Electrical Engineering courses at Sobral, Universidade Federal do Ceará - Campus Mucambinho, Rua Estanislau Frota, S/N, 62000 Sobral- CE, Brazil
  • Department of Electrical Engineering, Universidade Federal do Ceará – Campus do Pici, P.O.Box 6001 - Fortaleza-CE,Brazil
Bibliografia
  • [1] Kiyota K., and Chiba A. Design of switched reluctance motor competitive to 60-kw ipmsm in third-generation hybrid electric vehicle. IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 48:2303–2309, 2012.
  • [2] X. D. Xue, K. W. E. Cheng, J. K. Lin, Z. Zhang, K. F. Luk, T. W. Ng, and N. C. Cheung. Optimal control method of motoring operation for srm drives in electric vehicles. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 59:1191–1204, 2010.
  • [3] T. J. E Miller. Electronic Control of Switched Reluctance Machines. Newnes, Oxford, UK, 2001.
  • [4] Wieslaw Jazdzynski, Michal Majchrowicz. Analytical Model of a Switched Reluctance Motor for its Optimization – Selected Problems. PRZEGLĄD ELEKTROTECHNICZNY, R. 89 NR 11/2013: 153-158, 2013.
  • [5] Torrico B. C., Almeida R. N. C, dos Reis L. L. N., Silva W. A., and Pontes R. S. T. Robust control based on generalized predictive control applied to switched reluctance motor current loop. Journal of Dynamic Systems, Measurement and Control 136, 2012.
  • [6] Piotr. Bogusz. Analiza wpływu wybranych parametrów sterowania na właściwości napędu SRM pojazdu elektrycznego. PRZEGLĄD ELEKTROTECHNICZNY. R. 90 NR 2/2014: 161-164, 2014.
  • [7] Mehmet Gedikpinar. The speed control of DC motors with Support Vector Machine. PRZEGLĄD ELEKTROTECHNICZNY, R. 87 NR 5/2011: 269-271, 2011.
  • [8] X. D. Xue, K. W. E. Cheng, and S. L. Ho. Optimization and evaluation of torque-sharing functions for torque ripple minimization in switched reluctance motor drives. IEEE TRANSACTIONS ON POWER ELECTRONICS, 24:2076– 2090, 2009.
  • [9] Christopher A. Hudson, N. S. Lobo, and R. Krishnan. Sensorless control of single switch-based switched reluctance motor drive using neural network. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 55:321–329, 2008.
  • [10] Prashanth Krishnamurthy, Wenzhe Lu, Farshad Khorrami, and Ali Keyhani. Robust force control of an srm-based electromechanical brake and experimental results. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 17:1306–1317, 2009.
  • [11] J. C. Doyle and G. Stein. Robustness with observers. IEEE Transactions on Automatic Control, 24(24):607–611, 1979.
  • [12] Eduardo Fernández Camacho and Carlos Bordons. Model Predictive Control. Springer-Verlag, London, UK, 2nd edition, 2004.
  • [13] J. A. Rossiter. Model-based predictive control: a practical approach. CRC Press, Boca Raton - Florida, USA, 2002.
  • [14] J. M. Maciejowski. Asymptotic recovery for discrete-time systems. IEEE Transactions on Automatic Control, 30(6):602–605,1985.
  • [15] Jung Jun Park, Soohee Han, and Wook Hyun Kwon. Finite memory generalized predictive controls for discrete-time state space models. In International Conference on Control, Automation and Systems - Seoul, Korea, 2008.
  • [16] Thomas Kailath, Ali H Sayed, and Babak Hassibi. Linear estimation, volume 1. Prentice Hall Upper Saddle River, NJ, 2000.
  • [17] Sigurd Skogestad and Ian Postlethwaite. MULTIVARIABLE FEEDBACK CONTROL: Analysis and design. John Wiley & Sons, New York, USA, 2 edition, 2005.
  • [18] Gene F. Franklin, J. David Powell, and Michael L. Workman. Digital Control of Dynamic Systems. Addison-Wesley, Menlo Park, CA, USA, 1997.
  • [19] Sigurd Skogestad. Simple analytic rules for model reduction and pid controller tuning. Journal of Process Control, (13):291–309, 2003.
  • [20] B. P. Lathi. MODERN DIGITAL AND ANALOG COMMUNICATION SYSTEMS. Oxford University Press. 1995. NY USA.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-54371329-8ccf-4d4c-953d-b40c5411c2c4
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