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Estimation of state variables of the drive system with elastic joint using moving horizon estimation (MHE)

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Języki publikacji
EN
Abstrakty
EN
The article presents issues related to the application of a moving horizon estimator for state variables reconstruction in an advanced control structure of a drive system with an elastic joint. Firstly, a short review of the commonly used methods for state estimation in presented. Then, a description of a state controller structure follows. The design methodology based on the poles-placement method is briefly described. Next, the mathematical algorithm of MHE is presented and some crucial features of MHE are analysed. Then, selected simulation and experimental results are shown and described. The investigation shows, among others, the influence of window length on the quality of state variables estimation.
Rocznik
Strony
883--892
Opis fizyczny
Bibliogr. 25 poz., rys., tab.
Twórcy
autor
  • Wroclaw University of Science and Technology, Department of Electrical Machines, Drives and Measurements
Bibliografia
  • [1] R. Montague, C Bingham, and K. Atallah, “Servo Control of Magnetic Gears”, IEEE/ASME Transactions on Mechatronics17(2), 269‒278 (2012).
  • [2] R. Zhang and C. Tong, “Torsional vibration control of the main drive system of a rolling mill based on an extended state observer and linear quadratic control”, Journal of Vibration and Control, 12(3), 313‒327 (2006)
  • [3] K. Szabat and T. Orlowska-Kowalska, “Vibration Suppression in a Two-Mass Drive System Using PI Speed Controller and Additional Feedbacks – Comparative Study”, IEEE Transactions on Industrial Electronics, 54(2), 1193‒1206 (2007)
  • [4] K. Szabat and T. Orłowska-Kowalska, “Application of the Kal-man Filters to the High-Performance Drive System With Elas-tic Coupling”, IEEE Trans. on Industrial Electronics 59(11), 426‒4235 (2012).
  • [5] P. Serkies, “A novel predictive fuzzy adaptive controller for a two-mass drive system”, Bull. Pol. Ac.: Tech, 66(1), 37‒47, (2018).
  • [6] M. Cychowski and K. Szabat, “Efficient real-time model predictive control of the drive system with elastic transmission”, IET Control Theory & Applic., 4(1), 37‒49 (2010).
  • [7] M.A. Valenzuela, J.M. Bentley, and R.D. Lorenz, “Evaluation of Torsional Oscillations in Paper Machine Sections”, IEEE Trans-action on Industry Applications 2, 493‒501 (2005).
  • [8] C. Wang, M. Yang, W. Zheng, J. Long, and D. Xu, “Vibration Suppression with Shaft Torque Limitation Using Explicit MPC-PI Switching Control in elastic drive systems”, IEEE Trans. on Industrial Electronics, 62(11), 6855‒6867 (2015).
  • [9] K. Ito, K. Watanabe, and M. Iwasaki, “Robust load states estima-tion aginst mechanical parameters variation of a two-mass sys-tem using acceleration-aided dynamic Kalman filter”, IEEE 15th International Workshop on Advanced Motion Control (AMC), 491‒496, 2018.
  • [10] K. Szabat, T. Tran-Van, and M. Kamiński, “A Modified FuzzyLuenberger Observer for a Two-Mass Drive System”, IEEE Trans. on Industrial Informatics, 11(2), 531‒539, (2015).
  • [11] K. Dróżdż, “Adaptive control of the drive system with elasticcoupling using fuzzy Kalman filter with dynamic adaptation of selected coefficients”, Eksploatacja i Niezawodność – Maintenance and Reliability, 17(4), 561‒568 (2015).
  • [12] M. Kamiński and T. Orlowska-Kowalska, “Optimisation of neural state variables estimators of two-mass drive system using the Bayesian regularization method”, Bull. Pol. Ac.: Tech. 59(1), 33‒38, (2011)
  • [13] Y. Hori, H. Sawada, and Y. Chun, “Slow resonance ratio control for vibration suppression and disturbance rejection in torsional system”, IEEE Transaction on Industrial Electronics 46(1), 162‒168, (1999).
  • [14] Y. A.Thomas, “Linear quadratic optimal estimation and control with receding horizon”, Electron. Lett.11, 19‒21, (1975).
  • [15] J.B. Rawlings and B.R. Bakshi, “Particle filtering and moving horizon estimation”, Computers & Chemical Engineering, 30(10), 1529‒1541, (2006).
  • [16] S. Brock, D. Luczak, K. Nowopolski, T. Pajchrowski, and K. Zawirski, “Two Approaches to Speed Control for Multi-Mass System with Variable Mechanical Parameters”, IEEE Trans. on Industrial Electronics 64(4), 3338‒3347, (2017).
  • [17]S. Brock and K. Zawirski, “New approaches to selected problems of precise speed and position control of drives”, 38th Annual Conference on IEEE Industrial Electronics Society IECON 2012, 6291‒6296.
  • [18] D. Luczak and T. Pajchrowski, “Application of Adaptive Neural Controller and Filter Tune for Multi-Mass Drive System”, 20th European Conference on Power Electronics and Applications (EPE’18 ECCE Europe), P.1–P.9, 2018.
  • [19] C.V. Rao and J.B. Rawlings, J.H. Lee, “Constrained linear state estimation – a moving horizon approach”, Automatica 37(10), 1619‒1628 (2001).
  • [20] D. Sui, T. A. Johansen and L. Feng, “Linear moving horizon estimation with pre-estimating observer”. IEEE Trans. on Automatic Control 55(10), 2363‒2368 (2010).
  • [21] A.C. Rios-Coelhoa, W.F. Saccob, N. Hendersona, and A Metropolis algorithm combined with Hooke–Jeeves local search method applied to global optimization, Applied Mathematics and Com-putation217(2), 843‒853, (2010).
  • [22] K. Szabat and M. Kamiński,Designing a state controller in a drive system with a elastic coupling including the electromagnetic torque shaping loop (in Polish). Transactions on computer applications in electrical engineering: XIV Conference ZKwE ‘09, Poznan, April 20‒22, 2009, 277‒278.
  • [23] P. Dróżdż and K.Szabat, Speed control of a two-mass drive sys-tem using a sliding controller with an adaptive output filter (in Polish), Przegląd Elektrotechniczny93(9), 151‒154 (2017).
  • [24] J. Kabziński, Adaptive Control of Two-Mass Drive Systemwith Nonlinear Stiffness and Damping, IECON 2018 – 44th Annual Conference of the IEEE Industrial Electronics Society (2018).
  • [25] M. Kamiński and K. Najdek, Adaptive neural controller based on RBF model applied for electrical drive with PMSM motor (in Polish), Przegląd Elektrotechniczny94(6), 94‒98 (2018)
Uwagi
PL
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-2a6ab922-655a-4f16-a35a-172fbf5ea101
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