High-performance PMSM servo-drive with constrained state feedback position controller

• Autorzy: Tarczewski T. , Skiwski M. , Niewiara L. J. , Grzesiak L. M.

Identyfikatory

DOI

10.24425/119058

• Języki publikacji: EN

Abstrakty

EN

This paper describes high-performance permanent magnet synchronous motor (PMSM) servo-drive with constrained state feedback (SFC) position controller. Superior behavior of the control system has been achieved by applying SFC with constraints handling method based on a posteriori model predictive approach (MPAC). The concept utilizes predictive equations obtained from discrete-time model of the PMSM to compute control signals which generate admissible values of the future state variables. The novelty of the proposed solution lies in the limitation of several state-space variables in servo-drive control system. Since MPAC has firstly been applied to limit more than one state-space variable of the plant, necessary conditions for introducing constraints into multivariable control system with SFC are depicted. Due to the low complexity of proposed algorithm, a low cost microprocessor, STM32F4, is employed to execute the state feedback position control with model predictive approach to constraints handling. Experimental results show that the proposed control method provides superior performance of PMSM servodrive with modern SiC based voltage source inverter (VSI).

Słowa kluczowe

EN

constrained control; model predictive approach; permanent magnet synchronous motor; position control; state feedback control

PL

model predykcyjny; silnik synchroniczny z magnesem trwałym; sprzężenie zwrotne

• Wydawca: Polska Akademia Nauk, Wydział IV Nauk Technicznych
• Czasopismo: Bulletin of the Polish Academy of Sciences. Technical Sciences
• Rocznik: 2018
• Tom: Vol. 66, nr 1
• Strony: 49--58
• Opis fizyczny: Bibliogr. 32 poz., rys., wykr., tab.

Twórcy

autor

Tarczewski T.

• Department of Automatics and Measurement Systems, Nicolaus Copernicus Unversity, 5 Grudziadzka St., 87-100 Toruń, Poland

autor

Skiwski M.

• Department of Automatics and Measurement Systems, Nicolaus Copernicus Unversity, 5 Grudziadzka St., 87-100 Toruń, Poland

autor

Niewiara L. J.

• Department of Automatics and Measurement Systems, Nicolaus Copernicus Unversity, 5 Grudziadzka St., 87-100 Toruń, Poland

autor

Grzesiak L. M.

• Institute of Control and Industrial Electronics, Warsaw University of Technology, 75 Koszykowa St., 00-662 Warsaw, Poland

Bibliografia

• [1] F.F.M. El-Sousy, “Intelligent optimal recurrent wavelet Elman neural network control system for permanent-magnet synchronous motor servo drive”, IEEE Trans. Ind. Informat. 9 (4), 1986–2003, (2013).
• [2] S.M. Yang and K.W. Lin, “Automatic control loop tuning for permanent-magnet AC servo motor drives”, IEEE Trans. Ind. Electron. 63 (3), 1499–1506, (2016).
• [3] H. Chaoui, M. Khayamy, and A.A. Aljarboua, “Adaptive interval type-2 fuzzy logic control for pmsm drives with a modified reference frame”, IEEE Trans. Ind. Electron. 64 (5), 3786–3797, (2017).
• [4] K. Urbanski, “A new sensorless speed control structure for PMSM using reference model”, Bull. Pol. Ac.: Tech. 65 (4), 489–496, (2017).
• [5] M. Preindl and S. Bolognani, “Model predictive direct speed control with finite control set of PMSM drive systems”, IEEE Trans. Power Electron. 28 (2), 1007–1015, (2013).
• [6] M. Bouheraoua, J. Wang, and K. Atallah, “Design and implementation of an observer-based state feedback controller for a pseudo direct drive”, IET Electr. Power Appl. 7 (8), 643–653, (2013).
• [7] 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, (2016).
• [8] A. Królikowski and D. Horla, “Robustness of adaptive discretetime LQG control for first-order systems”, Bull. Pol. Ac.: Tech. 58 (1), 89–97, (2010).
• [9] M. Brasel, “A gain-scheduled multivariable LQR controller for permanent magnet synchronous motor”, in Proc. IEEE MMAR Conf., 722–725, (2014).
• [10] G.F. Franklin, J.D. Powell, and M.L. Workman, Digital Control of Dynamic Systems, Addison-Wesley, (1998).
• [11] B. Ufnalski, A. Kaszewski, and L.M. Grzesiak, “Particle swarm optimization of the multioscillatory LQR for a three-phase fourwire voltage-source inverter with an LC output filter”, IEEE Trans. Ind. Electron. 62 (1), pp. 484–493, (2015).
• [12] I. Robandi, K. Nishimori, and R. Nishimura, “Optimal feedback control design using genetic algorithm in multimachine power system”, Int. J. Elec. Power & En. Sys. 23 (4), 263–271, (2001).
• [13] F. Morel, X.F. Lin-Shi, and J.M. Retif, “A comparative study of predictive current control schemes for a permanent-magnet synchronous machine drive”, IEEE Trans. Ind. Electron. 56 (7), 2715–2728, (2009).
• [14] F. Blanchini and S. Miani, Set-Theoretic Methods in Control, Springer Science, (2007).
• [15] P.J. Serkies, “Predictive speed control in PMSM servo drive with elastic coupling at different blocking controls technique”, Przeglad Elektrotechniczny 91 (11), 271‒274, (2015) in Polish.
• [16] A. Damiano, G. Gatto, and I. Marongiu, “Operating constraints management of a surface-mounted pm synchronous machine by means of an FPGA-based model predictive control algorithm”, IEEE Trans. Ind. Informat. 10 (1), 243–255, (2014).
• [17] H. Liu and S. Li, “Speed control for PMSM servo system using predictive functional control and extended state observer”, IEEE Trans. Ind. Electron. 59 (2), 1171–1183, (2012).
• [18] C. Xia, X. Qiu, Z. Wang, and T. Shi, “Predictive torque control for voltage source inverter-permanent magnet synchronous motor based on equal torque effect”, IET Electr. Power Appl. 10 (3), 208–216, (2016).
• [19] Y. Chen, T.H. Liu, and C.F. Hsiao, “Implementation of adaptive inverse controller for an interior permanent magnet synchronous motor adjustable speed drive system based on predictive current control”, IET Electr. Power Appl. 9 (1), 60–70, (2015).
• [20] J.L. Chen and T.H. Liu, “Implementation of a predictive controller for a sensorless interior permanent-magnet synchronous motor drive system”, IET Electr. Power Appl. 6 (8), 513–525, (2012).
• [21] M.A. Stephens, C. Manzie, and M.C. Good, “Model predictive control for reference tracking on an industrial machine tool servo drive”, IEEE Trans. Ind. Informat. 9 (2), 808–816, (2013).
• [22] K.Y. Chen, “Sliding mode minimum-energy control for a mechatronic motor-table system”, IEEE/ASME Trans. on Mechatronics 21 (3), 1487–1495, (2016).
• [23] L.M. Grzesiak and T. Tarczewski, “PMSM servo-drive control system with a state feedback and a load torque feedforward compensation”, COMPEL 32 (1), 364–382, (2013).
• [24] T. Baumgartner and J.W. Kolar, “Multivariable state feedback control of a 500 000-r/min self-bearing permanent-magnet motor”, IEEE/ASME Trans. Mechatronics 20 (3), 1149–1159, (2015).
• [25] T. Tarczewski, L. Niewiara, M. Skiwski, and L. Grzesiak, “Gain-scheduled constrained state feedback control of DCDC buck power converter”, IET Power Electron., accepted manuscript, 1–9, DOI: 10.1049/iet-pel.2017.0370, (2017).
• [26] F. Borrelli and T. Keviczky, “Distributed LQR design for identical dynamically decoupled systems”, IEEE Trans. Autom. Control 53 (8), 1901–1912, (2008).
• [27] A. Tewari, Modern Control Design with Matlab and Simulink, John Wiley and Sons, (2002).
• [28] H.S. Lee and M. Tomizuka, “Robust motion controller design for high-accuracy positioning systems”, IEEE Trans. Ind. Electron. 43 (1), 48–55, (1996).
• [29] K. Jezernik and M. Rodic, “High precision motion control of servo drives”, IEEE Trans. Ind. Electron. 56 (10), 3810–3816, (2009).
• [30] 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).
• [31] P. Cortes, M.P. Kazmierkowski, and R. Kennel, “Predictive control in power electronics and drives”, IEEE Trans. Ind. Electron. 55 (12), 4312–4324, (2008).
• [32] 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).

Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).