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Semi-active control of ship mast vibrations using magneto-rheological dampers

  • Cheng, Y.S. (Department of Naval Architecture and Ocean Engineering, Huazhong University of Science and Technology) ;
  • Au, F.T.K. (Department of Civil Engineering, The University of Hong Kong) ;
  • Zhong, J.P. (Department of Naval Architecture and Ocean Engineering, Huazhong University of Science and Technology)
  • Received : 2007.12.03
  • Accepted : 2008.10.23
  • Published : 2008.12.20

Abstract

On marine vessels, delicate instruments such as navigation radars are normally mounted on ship masts. However the vibrations at the top of mast where the radar is mounted often cause serious deterioration in radar-tracking resolution. The most serious problem is caused by the rotational vibrations at the top of mast that may be due to wind loading, inertial loading from ship rolling and base excitations induced by the running propeller. This paper presents a method of semi-active vibration control using magneto-rheological (MR) dampers to reduce the rotational vibration of the mast. In the study, the classical optimal control algorithm, the independent modal space control algorithm and the double input - single output fuzzy control algorithm are employed for the vibration control. As the phenomenological model of an MR damper is highly nonlinear, which is difficult to analyse, a back- propagation neural network is trained to emulate the inverse dynamic characteristics of the MR damper in the analysis. The trained neural network gives the required voltage for each MR damper based on the displacement, velocity and control force of the MR damper quickly. Numerical simulations show that the proposed control methods can effectively suppress the rotational vibrations at the top of mast.

Keywords

References

  1. Bracewell, R.N. (1999), 'The Fourier Transform and its Applications', McGraw-Hill
  2. Bryson, A.E. and Ho, Y.C. (1975), 'Applied optimal control: optimization, estimation and control', Washington, D.C: Hemisphere Publishing Corporation
  3. Carlson, J.D. and Spencer, Jr., B.F. (1996), 'Magneto-rheological fluid dampers for semi-active seismic control', Proceeding of 3rd International Conference on Motion and Vibration Control. Chiba, Japan, September, III, 35-40
  4. Chang, C.C. and Roschke, P. (1999), 'Neural network modeling of a magnetorheological damper', J. Intel. Mater. Syst. Struct., 9(9), 755-764 https://doi.org/10.1177/1045389X9800900908
  5. Chang, C.C. and Zhou, L. (2002), 'Neural network emulation of inverse dynamics for a magnetorheological Damper', J. Struct. Eng., 128(2), 231-239 https://doi.org/10.1061/(ASCE)0733-9445(2002)128:2(231)
  6. Davenport, A.G. (1967), 'Gust loading factors', J. Struct. Div., 93(ST3), 11-34
  7. Dyke, S.J., Spencer, Jr., B.F., Sain, M.K., and Carlson, J.D. (1996), 'Modeling and control of magnetorheological dampers for seismic response reduction', Smart Mater. Struct., 5, 565-575 https://doi.org/10.1088/0964-1726/5/5/006
  8. Housner, G.W., Bergman, L.A., Caugher, T.K., Chassiakos, A.G., Claus, R.O., Masri, S.F., Skelton, R.E., Soong, T.T., Spencer, B.F., and Yao, J.T.P. (1997), 'Structural control: past, present, and future', J. Eng. Mech., 123(9), 897-971 https://doi.org/10.1061/(ASCE)0733-9399(1997)123:9(897)
  9. Hsueh, W.J. and Lee, Y.J. (1992), 'Active vibration control on the mast of warships', Int. Shipbuild. Prog., 39(417), 79-94
  10. Jansen, L.M. and Dyke, S.J. (2000), 'Semiactive control strategies for MR dampers: Comparative study', J. Eng. Mech., 126(8), 795-803 https://doi.org/10.1061/(ASCE)0733-9399(2000)126:8(795)
  11. Jung, H.J., Spencer, Jr., BF., and Lee, I.W. (2003), 'Control of seismically excited cable-stayed bridge employing magnetorheological fluid dampers', J. Struct. Eng., 129(7), 873-883 https://doi.org/10.1061/(ASCE)0733-9445(2003)129:7(873)
  12. Mamdani, E.H. (1974), 'Application of fuzzy algorithms for control of simple dynamic plant', Pro. Inst. Elect. Eng., 121(12), 1585-1588 https://doi.org/10.1049/piee.1974.0328
  13. Meirovitch, L. (1985), Introduction to Dynamics and Control, New York: Wiley
  14. Mohammed, A., Kenny, C.S. and Kwok, F.N. (2004), 'Active control of cross wind response of 76-story tall building using a fuzzy controller', Eng. Struct., 130(4), 492-498
  15. Shinozuka, M. and Deodatis, G. (1991), 'Simulation of stochastic process by spectral representation', Appl. Mech. Rev., 44(4), 191-203 https://doi.org/10.1115/1.3119501
  16. Spencer, Jr., B.F., Dyke, S.J., Sain, M.K., and Carlson, J.D. (1996), 'Phenomenological model for magnetorheological mampers', J. Eng. Mech., 123(3), 230-237
  17. Spencer, Jr., B.F. (1986), Reliability of Randomly Excited Hysteretic Structures. New York, Springer-Verlag
  18. Wang, J.Y., Ni, Y.Q., Ko, J.M., and Spencer, Jr., B.F. (2005), 'Magneto-rheological tuned liquid column dampers (MR-TLCDs) for vibration mitigation of tall buildings: Modelling and analysis of open-loop control source', Comput. Struct., 83(25-26), 2023-2034 https://doi.org/10.1016/j.compstruc.2005.03.011
  19. Xu, Y.L., Qu, W.L., and Ko, J.M. (2000), 'Seismic response control of frame structures using magnetorheological/ electrorheological dampers', Earthq. Eng. Struct. D, 29, 557-575 https://doi.org/10.1002/(SICI)1096-9845(200005)29:5<557::AID-EQE922>3.0.CO;2-X
  20. Yang, G.Q., Spencer, Jr., B.F., Jung, H.J., and Carloson, J.D. (2004), 'Dynamic modeling of large-scale magnetroheological damper systems for civil engineering applications', J. Eng. Mech., 130(9), 1107-1114 https://doi.org/10.1061/(ASCE)0733-9399(2004)130:9(1107)
  21. Zhu, W.Q., Luo, M., and Dong, L. (2004), 'Semi-active control of wind excited building structures using MR/ ER dampers', Prob. Eng. Mech., 19(3), 279-285 https://doi.org/10.1016/j.probengmech.2004.02.011

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