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PMSM drive with adaptive state feedback speed controller

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this paper, the issue related to control of the plant with nonconstant parameters is addressed. In order to assure the unchanged response of the system, an adaptive state feedback speed controller for permanent magnet synchronous motor is proposed. The model-reference adaptive system is applied while the Widrow-Hoff rule is used as adjustment mechanism of controller’s coefficients. Necessary modifications related to construction of the cost function and formulas responsible for adjustment of state feedback speed controller’s coefficients are depicted. The impact of adaptation gain, which is the only parameter in proposed adjustment mechanism, on system behaviour is experimentally examined. The discussion about computational resources consumption of the proposed adaptation algorithm and implementation issues is included. The proposed approach is utilized in numerous experimental tests on modern SiC based drive with nonconstant moment of inertia. Comparison between adaptive and nonadaptive control schemes is also shown.
Rocznik
Strony
1009--1017
Opis fizyczny
Bibliogr. 26 poz., rys., tab.
Twórcy
  • Department of of Automatics and Measurement Systems, Nicolaus Copernicus University in Torun, ul. Grudziadzka 5, 87-100 Torun, Poland
  • Department of of Automatics and Measurement Systems, Nicolaus Copernicus University in Torun, ul. Grudziadzka 5, 87-100 Torun, Poland
  • Institute of Control and Industrial Electronics, Warsaw University of Technology, ul. Koszykowa 75, 00-662 Warsaw, Poland
Bibliografia
  • [1] S. Morimoto, “Trend of permanent magnet synchronous machines”, IEEJ Trans. Electr. Electron. Eng. 2 (2), 101–108 (2007).
  • [2] C. Mi and M.A. Masrur, Hybrid electric vehicles: principles and applications with practical perspectives, John Wiley & Sons, 2017.
  • [3] T. Tarczewski, M. Skiwski, L.J. Niewiara, and L.M. Grzesiak, “High-performance PMSM servo-drive with constrained state feedback position controller”, Bull. Pol. Ac.: Tech. 63 (1), 49–58 (2018).
  • [4] X. Liu, D. Wang, and Z. Peng, “Cascade-Free Fuzzy Finite-Control-Set Model Predictive Control for Nested Neutral Point-Clamped Converters With Low Switching Frequency”, IEEE Trans. Control Syst. Technol. 27 (5), 2237–2244 (2019).
  • [5] T. Tarczewski and L.M. Grzesiak, “Constrained state feedback speed control of PMSM based on model predictive approach”, IEEE Trans. Ind. Electron. 63 (6), 3867–3875 (2015).
  • [6] D. Horla and A. Krolikowski, “LQG/LTR control of input-delayed discrete-time systems”, Bull. Pol. Ac.: Tech. 67 (6), 1049–1058 (2019).
  • [7] D. Dobrowolski, J. Dobrowolski, W. Piekarska, and S. Stępień, “Fast optimal feedback controller for electric linear actuator used in spreading systems of road spreaders”, Bull. Pol. Ac.: Tech. 67 (6), 1041–1047 (2019).
  • [8] T. Tarczewski and L.M. Grzesiak, “An application of novel nature-inspired optimization algorithms to auto-tuning state feedback speed controller for PMSM”, IEEE Trans. Ind. Appl. 54 (3), 2913–2925 (2018).
  • [9] T. Pajchrowski and K. Zawirski, “Application of artificial neural network for adaptive speed control of PMSM drive with variable parameters”, Compel-Int. J. Comp. Math. Electr. Electron. Eng. 32 (4), 1287–1299 (2013).
  • [10] T. Orlowska-Kowalska and M. Dybkowski, “Performance analysis of the sensorless adaptive sliding-mode neuro-fuzzy control of the induction motor drive with MRAS-type speed estimator”, Bull. Pol. Ac.: Tech. 60 (1), 61–70 (2012).
  • [11] T. Orlowska-Kowalska, M. Dybkowski, and K. Szabat, “Adaptive sliding-mode neuro-fuzzy control of the two-mass induction motor drive without mechanical sensors”, IEEE Trans. Ind. Electron. 57 (2), 553–564 (2009).
  • [12] A.K. Khalaji and S.A.A. Moosavian, “Robust adaptive controller for a tractor–trailer mobile robot”, IEEE-ASME Trans. Mechatron. 19 (3), 943–953 (2013).
  • [13] S. Vaidyanathan, “Adaptive controller and synchronizer design for the Qi-Chen chaotic system”, in Procedings of International Conference on Computer Science and Information Technology, 124–133 (2012).
  • [14] F.K. Yeh, “Sliding-mode adaptive attitude controller design for spacecrafts with thrusters”, IET Contr. Theory Appl. 4 (7), 1254–1264 (2010).
  • [15] L. Laurent, M. Fruchard, and A. Ferreira, “Adaptive controller and observer for a magnetic microrobot”, IEEE Trans. Robot. 29 (4), 1060–1067 (2013).
  • [16] J. Koller, “Learning to walk with an adaptive gain proportional myoelectric controller for a robotic ankle exoskeleton”, J. NeuroEng. Rehabil. 12 (1), 97 (2015).
  • [17] J. Fei and M. Xin, “An adaptive fuzzy sliding mode controller for MEMS triaxial gyroscope with angular velocity estimation”, Nonlinear Dyn. 70 (1), 97–109 (2012).
  • [18] K.J. Åström and B. Wittenmark, Adaptive control, Courier Corporation, 2013.
  • [19] K.S. Narendra, Applications of adaptive control, Elsevier, 2012.
  • [20] N. Hovakimyan and C. Cao, L1 Adaptive Control Theory: Guaranteed Robustness with Fast Adaptation, Society for Industrial and Applied Mathematics, 2010.
  • [21] R. Kumar, “Review on model reference adaptive system for sensorless vector control of induction motor drives”, IET Electr. Power Appl. 9 (7), 496–511 (2015).
  • [22] M. Kamiński, “Zastosowanie algorytmu BAT w optymalizacji obliczeń adaptacyjnego regulatora stanu układu dwumasowego”, Prz. Elektrotechniczny 93 (1), 300–304 (2017) [in Polish].
  • [23] R. Szczepanski, T. Tarczewski, and L.M. Grzesiak, “Adaptive state feedback speed controller for PMSM based on Artificial Bee Colony algorithm”, Appl. Soft. Comput. 83, 105644 (2019).
  • [24] B. Widrow and M.E. Hoff, “Adaptive switching circuits”, Stanford Univ., CA, Stanford Electronics Labs, no. TR-1553-1 (1960).
  • [25] R. Szczepanski, T. Tarczewski, and L.M. Grzesiak, “PMSM drive with adaptive state feedback speed controller”, in Procedings of Conference Sterowanie w Energoelektronice i Napędzie Elektrycznym (SENE 2019), 2019.
  • [26] G.F. Franklin, J.D. Powell, and M.L. Workman, Digital control of dynamic systems, Addison-Wesley, 1998.
Typ dokumentu
Bibliografia
Identyfikator YADDA
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