Smart Structures and Systems

Techno-Press (테크노프레스)
권호 표지
DOI QR코드

DOI QR Code

Nonlinear control of structure using neuro-predictive algorithm

  • Baghban, Amir (Department of Civil Engineering, Ferdowsi University of Mashhad) ;
  • Karamodin, Abbas (Department of Civil Engineering, Ferdowsi University of Mashhad) ;
  • Haji-Kazemi, Hasan (Department of Civil Engineering, Ferdowsi University of Mashhad)
  • Received : 2015.03.18
  • Accepted : 2015.12.05
  • Published : 2015.12.25
⟨ Previous Next ⟩

Abstract

A new neural network (NN) predictive controller (NNPC) algorithm has been developed and tested in the computer simulation of active control of a nonlinear structure. In the present method an NN is used as a predictor. This NN has been trained to predict the future response of the structure to determine the control forces. These control forces are calculated by minimizing the difference between the predicted and desired responses via a numerical minimization algorithm. Since the NNPC is very time consuming and not suitable for real-time control, it is then used to train an NN controller. To consider the effectiveness of the controller on probability of damage, fragility curves are generated. The approach is validated by using simulated response of a 3 story nonlinear benchmark building excited by several historical earthquake records. The simulation results are then compared with a linear quadratic Gaussian (LQG) active controller. The results indicate that the proposed algorithm is completely effective in relative displacement reduction.

Keywords

References

  1. Bani-Hani, K.A., Mashal, A. and Sheban, M.A. (2006), "Semi-active neuro-control for base-isolation system using magnetorheological (MR) dampers", Earthq. Eng. Struct. D., 35, 1119-1144. https://doi.org/10.1002/eqe.574
  2. Bazzuro, P. and Cornell, C.A. (1994), "Seismic hazard analysis of nonlinear structures I: methodology", J. Struct.Eng.- ASCE,120(11), 3320-3344. https://doi.org/10.1061/(ASCE)0733-9445(1994)120:11(3320)
  3. Camacho, E.F. and Bordons, C. (1999), Model Predictive Control, London: Springer.
  4. FEMA 356 (2000), Prestandard and commentary for the seismic rehabilation of buildings, Federal Emergency Management Agency.
  5. Gholampour, A.A., Ghassemieh, M. and Kiani, J. (2014), "State of the art in nonlinear dynamic analysis of smart structures with SMA members", Int. J. Eng. Sci., 75, 108-117. https://doi.org/10.1016/j.ijengsci.2013.11.010
  6. Jung, H.J., Lee, H.J., Yoon, W.H., Oh, J.W. and Lee, I.W. (2004), "Semiactive neurocontrol for seismic response reduction using smart damping strategy", J. Comput. Civil Eng., 18(3), 277-280. https://doi.org/10.1061/(ASCE)0887-3801(2004)18:3(277)
  7. Karamodin, A. and H-Kazemi, H. (2008), "Semi-active control of structures using neuro-predictive algorithm for MR dampers", J. Struct.Control Health Monit., 17(3), 237-253.
  8. Karamodin, A., Irani, F. and Baghban, A. (2012), "Effectiveness of a fuzzy controller on the damage index of nonlinear benchmark buildings", Scientia Iranica A, 19(1), 1-10. https://doi.org/10.1016/j.scient.2011.12.002
  9. Kim, B., Washington, G.N. and Yoon, H.S. (2013), "Active vibration suppression of a 1D piezoelectric bimorph structure using modelpredictive sliding mode control", Smart Struct. Syst., 11(6), 623-635. https://doi.org/10.12989/sss.2013.11.6.623
  10. Kumar, R., Singh, S.P. and Chandrawat, H.N. (2007), "MIMO adaptive vibration control of smart structures with quickly varying parameters: Neural networks vs classical control approach", J. Sound Vib., 307, 639-661. https://doi.org/10.1016/j.jsv.2007.06.028
  11. Kwon, O.S. and Elnashai, A. (2006), "The effect of material and ground motion uncertainty on the seismic vulnerability curves of RC structure", Eng. Struct., 28, 289-303. https://doi.org/10.1016/j.engstruct.2005.07.010
  12. Lee, H.J., Yang, Y.G., Jung, H.J., Spencer, B.F. and Lee, I.W. (2006), "Semi-active neurocontrol of a base isolated benchmark structure", Struct. Control Health Monit., 13, 682-692. https://doi.org/10.1002/stc.105
  13. Lopez-Almansa, F., Andrade, R., Rodellar, J. and Reinhorn A.M. (1994a), "Modal predictive control of structures. I: formulation", J. Eng. Mech. - ASCE, 120(8), 1743-1760. https://doi.org/10.1061/(ASCE)0733-9399(1994)120:8(1743)
  14. Lopez-Almansa, F., Andrade, R., Rodellar, J. and Reinhorn A.M. (1994b), "Modal predictive control of structures. II: implementation", J. Eng. Mech. - ASCE, 120(8), 1761-1772. https://doi.org/10.1061/(ASCE)0733-9399(1994)120:8(1761)
  15. Lu, L.Y., Lin, C.C., Lin, G.L. and Lin, C.Y. (2010), "Experiment and analysis of a fuzzy-controlled piezoelectric seismic isolation system", J. Sound Vib., 329, 1992-2014. https://doi.org/10.1016/j.jsv.2009.12.025
  16. Mei, G., Kareem, A. and Kantor, J.C. (2001), "Real-time model predictive control of structures under earthquakes", Earthq. Eng. Struct. D., 30, 995-1019. https://doi.org/10.1002/eqe.49
  17. Mei, G., Kareem, A. and Kantor, J.C. (2002), "Model predictive control of structures under earthquakes using acceleration feedback", J. Eng. Mech. - ASCE, 128(5), 574-585. https://doi.org/10.1061/(ASCE)0733-9399(2002)128:5(574)
  18. Ohtori, Y., Christenson, R.E., Spencer, B.F. and Dyke, S.J. (2004), "Benchmark control problems for seismically excited nonlinear buildings", J. Eng.Mech. - ASCE, 130(4), 366-387. https://doi.org/10.1061/(ASCE)0733-9399(2004)130:4(366)
  19. Padgett, J.E. and DesRoches, R. (2008), "Methodology for the development of analytical fragility curves for retrofitted bridges", Earthq. Eng. Struct. D., 37, 1157-1174. https://doi.org/10.1002/eqe.801
  20. Pourzeynali, S., Lavasani, H.H. and Modarayi, A.H. (2007), "Active control of high rise building structures using fuzzy logic and genetic Algorithms", Eng. Struct., 29, 346-357. https://doi.org/10.1016/j.engstruct.2006.04.015
  21. Qin, S.J. and Badgwell, T.J. (1996), "An overview of industrial model predictive control technology", Chemical Process Control-V Proceedings of AIChE Symposium Series 316, 93, 232-256.
  22. Reigles, D.G. and Symans, M.D. (2006), "Supervisory fuzzy control of a base-isolated benchmark building utilizing a neuro-fuzzy model of controllable fluid viscous dampers", Struct. Control Health Monit., 13, 724-747. https://doi.org/10.1002/stc.108
  23. Rodellar, J., Barbat, A.H. and Sanchez, J.M. (1987), "Predictive control of structures", J. Eng. Mech. - ASCE, 113(6), 797-812. https://doi.org/10.1061/(ASCE)0733-9399(1987)113:6(797)
  24. Sommerville, P., Smith, N., Punyamurthula, S. and Sun, J. (1997), Development of ground motion time histories for phase II of the FEMA/SAC steel project, SAC Background Document Report No. SAC/BD-97/04.
  25. Suhir, E. (2014), "Elastic stability of a compressed cantilever beam on an elastic foundation, with application to a dual-coated fiber-optic connector", Int. J. Eng. Sci., 83, 85-94. https://doi.org/10.1016/j.ijengsci.2014.06.005
  26. Xu, LH. and Li, ZX. (2011), "Model predictive control strategies for protection of structures during earthquakes", Struct. Eng. Mech., 40(2), 233-243. https://doi.org/10.12989/sem.2011.40.2.233
  27. Zhang, J., He, L., Wang, E. and Gao, R. (2008), "A LQR controller design for active vibration control of flexible structures", Comput. Intell. Ind. Appl., 1, 127-132.

Cited by

  1. An experimental study of vibration control of wind-excited high-rise buildings using particle tuned mass dampers vol.18, pp.1, 2016, https://doi.org/10.12989/sss.2016.18.1.093