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A new sensorless speed control structure for PMSM using reference model

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Języki publikacji
EN
Abstrakty
EN
In the paper a new sensorless control structure for the PMSM drive is presented. Such a structure is especially recommended for speed in the range of single revolutions per second (excluding standstill). The method uses a back EMF observer for position estimation. However, there is no need to estimate the speed. This is a big advantage because of possible irregularity of estimated back EMF in this speed range, which makes the calculation of speed difficult or impossible. The proposed structure is similar to the model following control, but the reference model attempts to track the motor operating point. The main idea is to utilize as a reference a model of the whole drive, including speed and current controllers and motor model. Such a model produces reference voltage for the real inverter. However, an extra unit – called rotator – is needed to provide precise control of direct axis current, which is sensitive to the improper position of the voltage vector. The rotator acts as a kind of compensator for error of position estimation.
Rocznik
Strony
489--496
Opis fizyczny
Bibliogr. 34 poz., rys., wykr.
Twórcy
autor
  • Institute of Control and Information Engineering, Poznan University of Technology, 3A Piotrowo St., 61-138 Poznan, Poland
Bibliografia
  • [1] H. Kim, J. Son, and J. Lee, “A high-speed sliding-mode observer for the sensorless speed control of a PMSM”, IEEE Transactions on Industrial Electronics 58 (9), 4069–4077 (2011).
  • [2] L. Li, G. Tan, J. Liu, and B. Kou, “Sensorless control of PMSM based on state observer and the parameter error analysis”, in IEEE International Conference on Power Electronics, Drives and Energy Systems, 1–8 (2012).
  • [3] W. Gao and Z. Guo, “Speed sensorless control of PMSM using model reference adaptive system and RBFN”, Journal of Networks 8 (2013).
  • [4] Y. Fan, L. Zhang, M. Cheng, and K. Chau, “Sensorless SVPWM-FADTC of a new flux-modulated permanent-magnet wheel motor based on a wide-speed sliding mode observer”, IEEE Transactions on Industrial Electronics 62, 3143–3151 (2015).
  • [5] T. Michalski, C. Lopez, A. Garcia, and L. Romeral, “Sensorless control of five phase PMSM based on extended Kalman filter”, 42nd Annual Conference of the IEEE Industrial Electronics Society, 2904–2909 (2016).
  • [6] X. Song, J. Fang, B. Han, and S. Zheng, “Adaptive compensation method for high-speed surface PMSM sensorless drives of EMFbased position estimation error”, IEEE Transactions on Power Electronics 31, 1438–1449 (2016).
  • [7] J. Guzinski and H. Abu-Rub, “Predictive current control implementation in the sensorless induction motor drive”, IEEE International Symposium on Industrial Electronics, 691–696 (2011).
  • [8] K. Urbanski, “Position estimation for PMSM drive equipped with the motor choke”, Przegląd Elektrotechniczny 4, 237–241 (2013).
  • [9] D. Janiszewski, “Load torque estimation for sensorless PMSM drive with output filter fed by PWM converter”, in 39th Annual Conference of the IEEE Industrial Electronics Society, 2953–2959 (2013).
  • [10] J. Salomaki, A. Piippo, M. Hinkkanen, and J. Luomi, “Sensorless vector control of PMSM drives equipped with inverter output filter”, 32nd Annual Conference on Industrial Electronics, 1059 –1064 (2006).
  • [11] S.-M. Gu, F.-Y. He, and H. Zhang, “Study on extend Kalman filter at low speed in sensorless PMSM drives”, in International Conference on Electronic Computer Technology, 311–316 (2009).
  • [12] S. Brock and J. Deskur, “A practical approach to compensation of torque ripple in high-precision permanent magnet motor drives”, in International Conference on Electrical Drives and Power Electronics, Dubrovnik (2005).
  • [13] P. Bogusz, “A switched reluctance motor control method limiting the maximum dc source current in the low-speed range”, Bull. Pol. Ac.: Tech. 64(1), 197–206, (2016).
  • [14] J. Wisniewski and W. Koczara, “The sensorless rotor position identification and low speed operation of the axial flux permanent magnet motor controlled by the novel PIPCRM method”, in IEEE Power Electronics Specialists Conference. PESC, 2008.
  • [15] R. Raute, C. Caruana, C. Spiteri Staines, J. Cilia, N. Teske, M. Sumner, and G. M. Asher, “A review of sensorless control in induction machines using hf injection, test vectors and PWM harmonics”, in Symposium on Sensorless Control for Electrical Drives, 47–55 (2011).
  • [16] M. Schroedl, “Sensorless control of AC machines at low speed and standstill based on the INFORM method”, in Conference Record of the 1996 IEEE Industry Applications Conference, 270–277 (1996).
  • [17] G. Xie, K. Lu, S. Dwivedi, R. Riber, and F. Blaabjerg, “Minimum voltage vector injection method for sensorless control of PMSM for low-speed operations”, IEEE Transactions on Power Electronics 31 (2), 1785‒1794 (2016).
  • [18] P. Pelczewski, W. Oberschelp, and U. Kunz, “Optimal model-following control of a positioning drive system with a permanent-magnet synchronous motor”, Control Theory and Applications, IEE Proceedings D 138, 267–273 (1991).
  • [19] X. Dong,W. Tianmiao,W. Hongxing, and L. Jingmeng, “Adaptive model following speed control method of permanent magnet synchronous motor”, in 4th IEEE Conference on Industrial Electronics and Applications, 721–725 (2009).
  • [20] J. Kang, X. Zeng, Y. Wu, and D. Hu, “Study of position sensorless control of PMSM based on MRAS”, in IEEE International Conference on Industrial Technology, 1–4 (2009).
  • [21] R. Mustafa, Z. Ibrahim, and J. Lazi, “Sensorless adaptive speed control for PMSM drives”, in Power Engineering and Optimization Conference, 511– 516 (2010).
  • [22] S. Li and H. Gu, “Fuzzy adaptive internal model control schemes for PMSM speed-regulation system”, IEEE Transactions on Industrial Informatics 8, 767–779 (2012).
  • [23] T. Tarczewski, L. Grzesiak, A. Wawrzak, K. Karwowski, and K. Erwinski, “A state-space approach for control of NPC type 3-level sine wave inverter used in FOC PMSM drive”, Bull. Pol. Ac.: Tech. 62(3), 439‒448 (2014).
  • [24] P. Vas, Sensorless Vector and Direct Torque Control, Monographs in Electrical and Electronic Engineering, Oxford- New York, Oxford University Press, 1998.
  • [25] D. Luenberger, “An introduction to observers”, IEEE Transactions on Automatic Control 16, 596–602 (1971).
  • [26] K. Urbanski and K. Zawirski, “Improved method for position estimation using a two-dimensional scheduling array”, Automatika – Journal for Control, Measurement, Electronics, Computing and Communications 56, 331–340 (2015).
  • [27] F. Benchabane, A. Titaouine, O. Bennis, K. Yahia, D. Taibi, and A. Guettaf, “Sensorless direct torque control for salientpole PMSM based on extended Kalman filter fed by AC/DC/AC converter”, Frontiers in Energy 6, 247–254 (2012).
  • [28] Z. Wang, Y. Zheng, Z. Zou, and M. Cheng, “Position sensorless control of interleaved CSI fed PMSM drive with extended Kalman filter”, IEEE Transactions on Magnetics 48, 3688–3691 (2012).
  • [29] K. Zawirski, D. Janiszewski, and R. Muszynski, “Unscented and extended Kalman filters study for sensorless control of PM synchronous motors with load torque estimation”, Bull. Pol. Ac.: Tech. 61 (4), 793–801 (2013).
  • [30] C. Zych, A. Wronska-Zych, J. Dudczyk, and A. Kawalec, “A correction in feedback loop applied to two-axis gimbal stabilization”, Bull. Pol. Ac.: Tech. 63 (1), 217–219 (2015).
  • [31] Y. Zhao, W. Qiao, and L. Wu, “Compensation algorithms for sliding mode observers in sensorless control of IPMSMs”, in Electric Vehicle Conference, 1 –7 (2012).
  • [32] Z. Qiao, T. Shi, Y. Wang, Y. Yan, C. Xia, and X. He, “New sliding-mode observer for position sensorless control of permanent-magnet synchronous motor”, IEEE Transactions on Industrial Electronics 60, 710–719 (2013).
  • [33] T. Bernardes, V. Foletto Montagner, H. Grundling, and H. Pinheiro, “Discrete-time sliding mode observer for sensorless vector control of permanent magnet synchronous machine”, IEEE Transactions on Industrial Electronics 61, 1679–1691 (2014).
  • [34] A. Accetta, M. Cirrincione, and M. Pucci, “Sensorless control of PMSM by a linear neural network: TLS EXIN neuron”, in 36th Annual Conference on IEEE Industrial Electronics Society, 974 –978 (2010).
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-46b6e078-20ac-413b-9b12-1b9325564a47
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