PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Design of simultaneous input-shaping-based SIRMs fuzzy control for double-pendulum-type overhead cranes

Autorzy
Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Overhead cranes are extensively employed but their performance suffers from the natural sway of payloads. Sometime, the sway exhibits double-pendulum motions. To suppress the motions, this paper investigates the design of simultaneous input-shaping-based fuzzy control for double-pendulum-type overhead cranes. The fuzzy control method is based on the single input-rule modules (SIRMs). Provided the all the system variables are measurable, the SIRMs fuzzy controller is designed at first. To improve the performance of the fuzzy controller, the simultaneous input shaper is adopted to shape the control command generated by the fuzzy controller. Compared with other two control methods, i.e., the SIRMs fuzzy control and the convolved input-shaping-based SIRMs fuzzy control, simulation results illustrate the feasibility, validity and robustness of the presented control method for the anti-swing control problem of double-pendulum-type overhead cranes.
Rocznik
Strony
887--896
Opis fizyczny
Bibliogr. 31 poz., rys., tab., wykr.
Twórcy
autor
  • School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, P.R. China
autor
  • College of Automation, Beijing Union University, Beijing 100101, P.R. China
autor
  • School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, P.R. China
autor
  • Department of Electrical Engineering Yeungnam University, Gyeongsan, R. Korea
Bibliografia
  • [1] J. Smoczek, “P1-TS fuzzy scheduling control system design using local pole placement and interval analysis”, Bull. Pol. Ac.: Tech. 62 (3), 455-464 (2014).
  • [2] J.Q. Yi, N. Yubazaki, and K. Hirota, “Anti-swing and positioning control of overhead traveling crane”, Information Sciences 155 (1-2), 1942 (2003).
  • [3] J. Smoczek, “Interval arithmetic-based fuzzy discrete-time crane control scheme design”, Bull. Pol. Ac.: Tech. 61 (4), 863-870 (2013).
  • [4] N. Sun, Y.C. Fang, and X.B. Zhang, “Energy coupling output feedback control of 4-DOF underactuated cranes with saturated inputs”, Automatica 49 (5), 1318-1325 (2013).
  • [5] Y.C. Fang, B.J. Ma, P.C. Wang, and X.B. Zhang, “A motion planning-based adaptive control method for an underactuated crane system”, IEEE Trans. on Control Systems Technology 20 (1), 241-248 (2012).
  • [6] X.B. Zhang, Y.C. Fang, and N. Sun, “Minimum-time trajectory planning for underactuated overhead crane systems with state and control constraints”, IEEE Trans. on Industrial Electronics 61 (12), 6915-6925 (2014).
  • [7] E. Maleki, W. Singhose, and S.S. Gurleyuk, “Increasing crane payload swing by shaping human operator commands”, IEEE Trans. on Human-Machine Systems 44 (1), 106-114, (2014).
  • [8] D.W. Qian, S.W. Tong, and J.Q. Yi, “Adaptive control based on incremental hierarchical sliding mode for overhead crane systems”, Applied Mathematics and Information Sciences 7 (4), 1359-1364 (2013).
  • [9] D.W. Qian and J.Q. Yi, “Design of combining sliding mode controller for overhead crane systems”, Int. J. Control and Automation 6 (1), 131-140 (2013).
  • [10] M.S. Park, D. Chwa, and M. Eom, “Adaptive sliding-mode antisway control of uncertain overhead cranes with high-speed hoisting motion”, IEEE Trans. on Fuzzy Systems 22 (5), 1262-1271 (2014).
  • [11] E.M. Abdel-Rahman, A.H. Nayfeh, and Z.N. Masoud, “Dynamics and control of cranes: a review”, J. Vibration and Control 9 (7), 863-908 (2003).
  • [12] W.E. Singhose and S.T. Towell, “Double-pendulum gantry crane dynamics and control”, Proc. IEEE Conf. on Control Applications 1, 1205-1209 (1998).
  • [13] W. Singhose, D.R. Kim, and M. Kenison, “Input shaping control of double-pendulum bridge crane oscillations”, J. Dynamic Systems, Measurement and Control 130 (3), DOI: 10.1115/1.2907363 (2008).
  • [14] S. Lahres, H. Aschemann, O. Sawodny, and E.P. Hofer, “Crane automation by decoupling control of a double pendulum using two translational actuators”, Proc. American Control Conf. 1, 1052-1056 (2000).
  • [15] D.T. Liu,W.P. Guo, and J.Q. Yi, “Dynamics and GA-based stable control for a class of underactuated mechanical systems”, Int. J. Control, Automation and Systems 6 (1), 35-43 (2008).
  • [16] W. O’Connor and H. Habibi, “Gantry crane control of a double-pendulum, distributed-mass load, using mechanical wave concepts”, Mechanical Sciences 4b (2), 251-261 (2013).
  • [17] L.A. Tuan and S.G. Lee, “Sliding mode controls of doublependulum crane systems”, J. Mechanical Science and Technology 27 (6), 1863-1873 (2013).
  • [18] Y. Dong, Z. Wang, Z. Feng, and J. Cheng, “Incremental sliding mode control for double-pendulum-type overhead crane system”, Proc. 27th Chinese Control Conf. 1, 368-371 (2008).
  • [19] J. Vaughan, D.R. Kim, and W. Singhose, “Control of tower cranes with double- pendulum payload dynamics”, IEEE Trans Control Systems Technology 18 (6), 1345-1358 (2010).
  • [20] D.R. Kim and W. Singhose, “Performance studies of human operators driving double- pendulum bridge cranes”, Control Engineering Practice 18 (6), 567-576 (2010).
  • [21] E. Maleki and W. Singhose, “Swing dynamics and inputshaping control of human-operated double-pendulum boom cranes”, J. Computational and Nonlinear Dynamics 7 (3) DOI:10.1115/1.4005933 (2012).
  • [22] D. Blackburn, W. Singhose, and J. Kitchen, “Command shaping for nonlinear crane dynamics”, J. Vibration and Control 16 (4), 1-25 (2010).
  • [23] Z. Masoud, K. Alhazza, E. Abu-Nada, and M. Majeed, “A hybrid command-shaper for double-pendulum overhead cranes”, J. Vibration and Control 20 (1), 24-37 (2014).
  • [24] M. Adeli, S.H. Zarabadi, H. Zarabadipour, and M.A. Shoorehdeli, “Design of a parallel distributed fuzzy LQR controller for double-pendulum-type overhead cranes”, Proc. IEEE Int. Conf. on Control System, Computing and Engineering 1, 62-67 (2011).
  • [25] A. Niewiadomski and M. Kacprowicz, “Higher order fuzzy logic in controlling selective catalytic reduction systems”, Bull. Pol. Ac.: Tech. 62 (4), 743-750 (2014).
  • [26] S. Osowski, K. Brudzewski, and L.T. Hoai, “Modified neurofuzzy TSK network and its application in electronic nose”, Bull. Pol. Ac.: Tech. 61 (3), 675-680 (2013).
  • [27] J. Yi, N. Yubazaki, and K. Hirota, “A proposal of SIRMs dynamically connected fuzzy inference model for plural input fuzzy control”, Fuzzy Sets and Systems 125 (1), 79-92 (2002).
  • [28] H. Seki and M. Mizumoto, “SIRMs connected fuzzy inference method adopting emphasis and suppression”, Fuzzy Sets and Systems 215 (16), 112-126 (2013).
  • [29] S.W. Tong and D.W. Qian, “Control of a fuel cell based on the SIRMs fuzzy inference model”, Int. J. Hydrogen Energy 38 (10), 4124-4131 (2013).
  • [30] S.H. Lau, C.K. Ng, and K.M. Tay, “Data-driven SIRMsconnected FIS for prediction of external tendon stress”, Computers and Concrete, Int. J. 15 (1), 55-71 (2015).
  • [31] L. Cheng, Z.G. Hou, M. Tan, and W. Zhang, “Tracking control of a closed-chain five-bar robot with two degrees of freedom by integration of approximation-based approach and mechanical design”, IEEE Trans. Systems, Man, and Cybernetics, Part B: Cybernetics 42 (5), 1470-1479 (2012).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-dd964c58-30f8-459b-826e-14e1a3dbf9ab
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.