Smart Structures and Systems

  • 제11권3호
  • /
  • Pages.315-329
  • /
  • 2013
  • /
  • 1738-1584(pISSN)
  • /
  • 1738-1991(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

A nonlinear structural experiment platform with adjustable plastic hinges: analysis and vibration control

  • Li, Luyu (Department of Mechanical Engineering, University of Houston) ;
  • Song, Gangbing (Department of Mechanical Engineering, University of Houston) ;
  • Ou, Jinping (School of Civil Engineering, Dalian University of Technology)
  • 투고 : 2012.06.11
  • 심사 : 2012.11.30
  • 발행 : 2013.03.25
⟨ 이전 논문 다음 논문 ⟩

초록

The construction of an experimental nonlinear structural model with little cost and unlimited repeatability for vibration control study represents a challenging task, especially for material nonlinearity. This paper reports the design, analysis and vibration control of a nonlinear structural experiment platform with adjustable hinges. In our approach, magnetorheological rotary brakes are substituted for the joints of a frame structure to simulate the nonlinear material behaviors of plastic hinges. For vibration control, a separate magnetorheological damper was employed to provide semi-active damping force to the nonlinear structure. A dynamic neural network was designed as a state observer to enable the feedback based semi-active vibration control. Based on the dynamic neural network observer, an adaptive fuzzy sliding mode based output control was developed for the magnetorheological damper to suppress the vibrations of the structure. The performance of the intelligent control algorithm was studied by subjecting the structure to shake table experiments. Experimental results show that the magnetorheological rotary brake can simulate the nonlinearity of the structural model with good repeatability. Moreover, different nonlinear behaviors can be achieved by controlling the input voltage of magnetorheological rotary damper. Different levels of nonlinearity in the vibration response of the structure can be achieved with the above adaptive fuzzy sliding mode control algorithm using a dynamic neural network observer.

키워드

참고문헌

  1. Battaini, M. Yang, G. and Spencer Jr., B.F. (2000), "Bench-scale experiment for structural control", J. Eng. Mech.-ASCE, 126(2), 140-148. https://doi.org/10.1061/(ASCE)0733-9399(2000)126:2(140)
  2. Harris, H.G., Sabnis, G.M. and White, R.N. (1999), Structural modeling and experimental techniques, CRC Press.
  3. Kwak, M.K. and Sciulli, D. (1996), "Fuzzy-logic based vibration suppression control experiments on active structures", J. Sound Vib., 191(1), 15-28. https://doi.org/10.1006/jsvi.1996.0104
  4. Li, L.Y. and Ou, J.P. (2006a), "Magnetorheological damper control and simulation analysis for vibration reduction of nonlinear structure based on AFSMC algorithm", Earthq. Eng. Vib., 26(2), 96-103
  5. Li, L.Y. and Ou, J.P. (2006b), "Adaptive fuzzy sliding mode control for nonlinear vibration reduction of structure", J. Vib. Eng., 19(3), 319-325.
  6. Li, L.Y. and Ou, J.P. (2006c), "Dynamical neural network observer design for the nonlinear vibration model of structure", Proceedings of the 4th China-Japan-US Symposium of Structural Control and Monitoring, Hangzhou, China.
  7. Li, L.Y., Song, G. and Ou, J.P. (2010), "Nonlinear structural vibration suppression using dynamic neural network observer and adaptive fuzzy sliding mode control", J. Vib. Control, 16(10), 1503-1526. https://doi.org/10.1177/1077546309103284
  8. Li, X.L. and Li, H.N. (2005), "Experiment study control of frame-shear wall eccentric structure using MRD", J. Harbin Inst. Technol., 37(3), 147-150.
  9. MR Rotary Brake RD-2087-01. Lord Corporation.
  10. Ng, C.L. and Xu, Y.L. (2006), "Seismic response control of a building complex utilizing passive friction damper: experimental investigation", Earthq. Eng. Struct. D., 35(6), 657-677. https://doi.org/10.1002/eqe.549
  11. Ohtori, Y. Christenson, R.E. Spencer Jr., B.F. and Dyke, S.J. (2004), "Benchmark control problems for seismically excited nonlinear buildings", J. Eng. Mech.-ASCE, 130(4), 366-385. https://doi.org/10.1061/(ASCE)0733-9399(2004)130:4(366)
  12. Preumont, A. and Bossens, F. (2000), "Active tendon control of vibration of truss structures: theory and experiments", J. Intell. Mater. Syst. Struct., 11(2), 91-99. https://doi.org/10.1177/104538900772664288
  13. Reynolds, W.E. and Christenson, R.E. (2006), "Bench-scale nonlinear test structure for structural control research", Eng. Struct., 28, 1182-1189. https://doi.org/10.1016/j.engstruct.2005.12.007
  14. Soong, T.T. (1998), "Experimental simulation of degrading structures through active control", Earthq. Eng. Struct. D., 27(2), 143-154. https://doi.org/10.1002/(SICI)1096-9845(199802)27:2<143::AID-EQE721>3.0.CO;2-7
  15. Tse, T. and Chang, C.C. (2004), "Shear-mode rotary magnetorheological damper for small-scale structural control experiments", J. Struct. Eng.-ASCE, 130(6), 904-911. https://doi.org/10.1061/(ASCE)0733-9445(2004)130:6(904)
  16. Yi, F., Dyke, S.J., Caicedo, J.M. and Carlson, J.D. (2001), "Experimental verification of multiinput seismic control strategies for smart dampers", J. Eng. Mech.-ASCE, 127(11), 1152-1164. https://doi.org/10.1061/(ASCE)0733-9399(2001)127:11(1152)

피인용 문헌

  1. An evolutionary fuzzy modelling approach and comparison of different methods for shear strength prediction of high-strength concrete beams without stirrups vol.14, pp.5, 2014, https://doi.org/10.12989/sss.2014.14.5.785
  2. Study of a smart platform based on backstepping control method vol.16, pp.3, 2017, https://doi.org/10.1007/s11803-017-0398-5
  3. Development and Hybrid Position/Force Control of a Dual-Drive Macro-Fiber-Composite Microgripper vol.18, pp.4, 2018, https://doi.org/10.3390/s18041301