PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Fuzzy adaptive control of nonlinear two-mass system

Autorzy
Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In the paper, an adaptive control MRAS-based structure for nonlinear two-mass system is proposed. The performance of the control structure is supported by additional compensator. After short introduction a mathematical model of the drive system is presented. In the plant, the additional nonlinearities such as friction and mechanical hysteresis are considered. Then the structure of the fuzzy system is shown. Contrary to the majority of papers the controller considered is based on the II type fuzzy sets. Then the simulation tests showing performance of the proposed structure are presented. The drive is tested at different operation points, including low-speed region where friction plays dominant role. A comparison of classical PI controller with antiwindup and the proposed structure is presented. Then laboratory set-up with DC motor is described briefly. Experimental results are included in the paper. It is shown that the torsional vibrations of two-mass system are damped effectively. The impact of the existing delays of system is discussed. A summary is given at the end of the paper.
Wydawca
Rocznik
Strony
133--146
Opis fizyczny
Bibliogr. 15 poz., rys.
Twórcy
autor
  • Department of Electrical Machines, Drives and Measurements, Wrocław University of Science and Technology, Wrocław, Poland
Bibliografia
  • [1] WAI R., LIN C.M., HSU C.F., Adaptive fuzzy sliding-mode control for electrical servo drive, Fuzzy Sets and Systems, 2004, 143, 2, 295–310.
  • [2] PILTAN F., SULAIMAN N., ALLAHDADI S., DIALAME M., ZARE A., Position Control of Robot Manipulator: Design a Novel SISO Adaptive Sliding Mode Fuzzy PD Fuzzy Sliding Mode Control, Int. Journal of Artificial Intelligence and Expert System, 2011, 2, 5, 208–228.
  • [3] KNYCHAS S., DERUGO P., SZABAT K., Damping of the torsional vibration using adaptive fuzzy control system with different recurrences, 2014 IEEE 23rd International Symposium on Industrial Electronics (ISIE), Istambul, 2014, 1526–1531.
  • [4] DERUGO P., KACERKA J., JASTRZĘBSKI M., SZABAT K., Analiza ARN-R PID z warstwą tranzycji Petriego, w sterowaniu silnikiem liniowym z magnesami trwałymi, Poznań University of Technology Academic Journals, 2015, 83, 2015, 31–38.
  • [5] DERUGO P., KACERKA J., SZABAT K., Adaptacyjny regulator neuronowo-rozmyty z rekurencjami i warstwą tranzycji Petriego w sterowaniu napędem elektrycznym, Przegląd Elektrotechniczny, 2016, 92, 4, 79–84.
  • [6] SZABAT K., ORŁOWSKA-KOWALSKA T., Vibration Suppression in a Two-Mass Drive System Using PI Speed Controller and Additional Feedbacks – Comparative Study, IEEE Trans. on Industrial Electronics, 2007, 54, 2, 1193–1206.
  • [7] ORŁOWSKA-KOWALSKA T., DYBKOWSKI M., SZABAT K., Adaptive Sliding-Mode Neuro-Fuzzy Control of the Two-Mass Induction Motor Drive Without Mechanical Sensors, IEEE Transactions on Industrial Electronics, 2009, 57, 2, 553–564.
  • [8] SERKIES P., SZABAT K., Application of the MPC to the Position Control of the Two-Mass Drive System, IEEE Transactions on Industrial Electronics, 2012, 60, 9, 3679–3688.
  • [9] KAROLEWSKI B., Modelowanie więzów łączących elementy układu napędowego, Przegląd Elektrotechniczny, 2001, 77, 2, 39–43.
  • [10] OLSSON H., ASTROM K.J., CANUDAS de WIT C., GAFVERT M., LISCHINSKY P., Friction Models and Friction Compensation, European Journal of Control, 1998, 4, 3, 176–195.
  • [11] CILIZ M.K., TOMIZUKA M., Friction modeling and compensation for motion control using hybrid neural network models, Engineering Application of AI, 2007, 20, 7, 898–911.
  • [12] BONA B., INDRI, M., Friction Compensation in Robotics: an Overview, IEEE Conference on Decision and Control, 2005, 4360–4367.
  • [13] LIN F.J., FUNG R.F., WAI R.J., Comparison of sliding-mode and fuzzy neural network control for motor-toggle servomechanism, IEEE Trans. Mechatronics, 1998, 3, 4, 302–318.
  • [14] SZABAT K., KAMIŃSKI M., ORŁOWSKA-KOWALSKA T., Robust Control of an Electrical Drive using Adaptive Fuzzy Logic Control Structure with Sliding-Mode Compensator, The International Conference on “Computer as a Tool” EUROCON, 2007, Warsaw, 1706–1711.
  • [15] WRÓBEL K., Adaptive fuzzy control based on sets of the second type of the complex drive system operating at low speed, Scientific Papers of the Institute of Electrical Machines, Drives and Measurements of the Wrocław University of Technology, Studies and Research, 2015, 71, 35, 109–117.
Uwagi
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-94c4a51a-1c05-4a0b-9c87-47ffcb96a922
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.