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Artificial bee colony based state feedback position controller for PMSM servo-drive – the efficiency analysis

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Języki publikacji
EN
Abstrakty
EN
This paper presents a state feedback controller (SFC) for position control of PMSM servo-drive. Firstly, a short review of the commonly used swarm-based optimization algorithms for tuning of SFC is presented. Then designing process of current control loop as well as of SFC with feedforward path is depicted. Next, coefficients of controller are tuned by using an artificial bee colony (ABC) optimization algorithm. Three of the most commonly applied tuning methods (i.e. linear-quadratic optimization, pole placement technique and direct selection of coefficients) are used and investigated in terms of positioning performance, disturbance compensation and robustness against plant parameter changes. Simulation analysis is supported by experimental tests conducted on laboratory stand with modern PMSM servo-drive.
Rocznik
Strony
997--1007
Opis fizyczny
Bibliogr. 33 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] J. Staszak, K. Ludwinek, Z. Gaw ̨ ecki, J. Kurkiewicz, T. Bekier, and M. Jaśkiewicz, “Utilization of permanent magnet synchronous motors in industrial robots”, 2015 International Conference on Information and Digital Technologies, Zilina, 2015, pp. 342–347, doi: 10.1109/DT.2015.7222995.
  • [2] K. Pietrusiewicz, “Multi-degree of freedom robust control of the CNC XY table PMSM-based feed-drive module”, Archives of Electrical Engineering 61 (1), 15–31 (2012).
  • [3] B. Broel-Plater and K. Jaroszewski, “Improving the quality of the classic servo drive by modifying the motion control algorithm,” 2017 22nd International Conference on Methods and Models in Automation and Robotics (MMAR), Miedzyzdroje, 2017, pp. 43–46, doi: 10.1109/MMAR.2017.8046795.
  • [4] S. Brock, D. Łuczak, T. Pajchrowski, and K. Zawirski, “Selected methods for a robust control of direct drive with a multi-mass mechanical load”, in: J. Kabziński, ed., Advanced Control of Electrical Drives and Power Electronic Converters, Studies in Systems, Decision and Control, Springer, 75–98 (2017).
  • [5] K. Urbanski, “A new sensorless speed control structure for PMSM using reference model”, Bull. Pol. Ac.: Tech. 65 (4), 489–496 (2017).
  • [6] K. Dąbała and M. P. Kazmierkowski, “Converter-fed electric vehicle (car) drives–a critical review”, Przegląd Elektrotechniczny 95 (9), 1–12 (2019).
  • [7] L. Jarzebowicz, “Errors of a Linear Current Approximation in High-Speed PMSM Drives”, IEEE Trans. on Power Electron. 32 (11), 8254–8257 (2017).
  • [8] A.R. Ghafari-Kashani, J. Faiz, and M.J. Yazdanpanah, “Integration of non-linear H∞ and sliding mode control techniques for motion control of a permanent magnet synchronous motor”, IET Electric Power Applications 4 (4), 267–280 (2010).
  • [9] Z. Yin, L. Gong, C. Du, J. Liu and, Y. Zhong, “Integrated Position and Speed Loops Under Sliding-Mode Control Optimized by Differential Evolution Algorithm for PMSM Drives”, IEEE Trans. Pow. Electron. 34 (9), 8994–9005 (2019).
  • [10] K.A. Abuhasel, F.F.M. El-Sousy, M.F. El-Naggar, and A. Abu-Siada, “Adaptive RCMAC Neural Network Dynamic Surface Control for Permanent-Magnet Synchronous Motors Driven Two-Axis X-Y Table”, IEEE Access 7, 38068–38084 (2019).
  • [11] S. Mandra, K. Galkowski, E. Rogers, A. Rauh, and H. Aschemann, “Performance-Enhanced Robust Iterative Learning Control With Experimental Application to PMSM Position Tracking”, IEEE Trans. Control Syst. Technol. 27 (4), 1813–1819 (2019).
  • [12] M. Brasel, “A gain-scheduled multivariable LQR controller for permanent magnet synchronous motor”, 2014 19th International Conference on Methods and Models in Automation and Robotics (MMAR), Miedzyzdroje, 2014, pp. 722–725, doi: 10.1109/MMAR.2014.6957443.
  • [13] M. Safonov and M. Athans, “Gain and phase margin for multiloop LQG regulators”, IEEE Trans. Autom. Control 22 (2), 173–179 (1977).
  • [14] 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 66 (1), 49–58 (2018).
  • [15] A. Apte, V. Joshi, H. Mehta, and R. Walambe, “Disturbance Observer based Sensorless Control of PMSM using Integral State Feedback Controller”, IEEE Trans. Pow. Electron. 35 (6), 6082–6090 (2020), doi: 10.1109/TPEL.2019.2949921.
  • [16] S. Carriere, S. Caux, and M. Fadel, “Optimised speed control in state space for PMSM direct drives”, IET El. Pow. Applicat. 4 (3), 158–168 (2010).
  • [17] K. Paponpen and M. Konghirun, “LQR state feedback controller based on particle swarm optimization for IPMSM drive system”, 2015 IEEE 10th Conference on Industrial Electronics and Applications (ICIEA), Auckland, 2015, pp. 1175–1180, doi: 10.1109/ICIEA.2015.7334285.
  • [18] I. Robandi, K. Nishimori, R. Nishimura, and N. Ishihara, “Optimal feedback control design using genetic algorithm in multimachine power system”, Int. J. Elect. Power Energy Syst. 23 (4), 263–271 (2001).
  • [19] T. Tarczewski, M. Skiwski, L.M. Grzesiak, and M. Zielinski, “Constrained state feedback control of PMSM servo-drive”, Przegląd Elektrotechniczny 94 (3), 99–105 (2018).
  • [20] M. I. Solihin, Wahyudi, A. Legowo and R. Akmeliawati, “Comparison of LQR and PSO-based state feedback controller for tracking control of a flexible link manipulator”, 2010 2nd IEEE International Conference on Information Management and Engineering, Chengdu, 2010, pp. 354–358, doi: 10.1109/ICIME.2010.5477850.
  • [21] T. Tarczewski, L.J. Niewiara, and L.M. Grzesiak, “Auto-tuning of state feedback position controller for PMSM servo-drive – the efficiency analysis”, in Proc. SENE Conf., 2019.
  • [22] K. Dróżdż, M. Kamiński, P.J. Serkies, and K. Szabat, “Application of neural networks for state variables estimation if drive with permanent manget synchronous motor”, Scientific Papers of The Institute of Electrical Machines, Drives and Measurements of the Wrocław University of Science and Technology Series: Studies and Research 69 (33), 132–140 (2013).
  • [23] L. Harnefors H.-P. and Nee, “Model-Based Current Control of AC Machines Using the Internal Model Control Method”, IEEE Trans. Ind. Appl. 34 (1), 133–141 (1998).
  • [24] H.-B. Shin and J.-G. Park, “Anti-windup PID controller with integral state predictor for variable-speed motor drives”, IEEE Trans. Ind. Electron. 59 (3), 1509–1516 (2012).
  • [25] M. Kamiński, “Application of the BAT algorithm in optimization of adaptive state space controller used for two-mass system”, Przegląd Elektrotechniczny 93 (1), 300–304 (2017).
  • [26] K. Jezernik and M. Rodic, “High precision motion control of servo drives”, IEEE Trans. Ind. Electron. 56 (10), 3810–3816 (2009).
  • [27] D.C. Lee, S.K. Sul, and M.H. Park, “High performance current regulator for a field-oriented controlled induction motor drive”, IEEE Trans. Ind. Appl. 30 (5), 1247–1257 (1994).
  • [28] J. Kabziński, P. Mosiołek, and M. Jastrz ̨ ebski, “Adaptive Position Tracking with Hard Constraints – Barrier Lyapunov Functions Approach”, in: Kabziński J. (eds) Advanced Control of Electrical Drives and Power Electronic Converters. Studies in Systems, Decision and Control, vol. 75, Springer, Cham (2017).
  • [29] J. Kabziński and P. Mosiołek, “Adaptive control of motion with hard constraints, based on nonlinear state transformation”, Bull. Pol. Ac.: Tech. 68 (5), (2020).
  • [30] Kim Mun-Soo et al., “A robust control of permanent magnet synchronous motor using load torque estimation”, ISIE 2001. 2001 IEEE International Symposium on Industrial Electronics Proceedings (Cat. No.01TH8570), Pusan, South Korea, 2001, pp. 1157–1162 vol. 2, doi: 10.1109/ISIE.2001.931642.
  • [31] R. Szczepanski, T. Tarczewski, K. Erwinski, and L.M. Grzesiak, “Comparison of Constraint-handling Techniques Used in Artificial Bee Colony Algorithm for Auto-Tuning of State Feedback Speed Controller for PMSM”, in Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics – Volume 2: ICINCO, 2018, pp. 269–276, doi: 10.5220/0006904002790286.
  • [32] D. Karaboga and B. Basturk, “On the performance of artificial bee colony (ABC) algorithm”, Appl. Soft. Comput. 8 (1), 687–697 (2008).
  • [33] T. Tarczewski, M. Skiwski, L.M. Grzesiak, and M. Zieliński, “PMSM Servo-Drive Fed by SiC MOSFETs Based VSI”, Power Electronics and Drives 3 (1), 35–45 (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-0da715fe-465f-4584-8e46-5a717ad89107
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