DOI QR코드

DOI QR Code

Design of intelligent control strategies using a magnetorheological damper for span structure

  • Hernandez, Angela (Departamento de Ingenieria de Sistemas y Automatica, Arquitectura y Tecnologia de Computadoras, Universidad de La Laguna, Edificio de Fisica y Matematicas C/ Astrofisico Francisco Sanchez) ;
  • Marichal, Graciliano N. (Departamento de Ciencias de la Navegacion, Ingenieria Maritima, Agraria e Hidraulica, Escuela Tecnica Superior de Nautica, Maquinas y Radioelectronica Naval, Universidad de La Laguna) ;
  • Poncela, Alfonso V. (Instituto de las Tecnologias Avanzadas de la Produccion, ITAP, Universidad de Valladolid) ;
  • Padron, Isidro (Departamento de Ciencias de la Navegacion, Ingenieria Maritima, Agraria e Hidraulica, Escuela Tecnica Superior de Nautica, Maquinas y Radioelectronica Naval, Universidad de La Laguna)
  • Received : 2013.07.26
  • Accepted : 2013.12.17
  • Published : 2015.04.25

Abstract

This paper focuses on the design of an intelligent control system. The used techniques are based on Neuro Fuzzy approaches applied to a magnetorheological damper in order to reduce the vibrations over footbridges; it has been applied to the Science Museum Footbridge of Valladolid, particularly. A model of the footbridge and of the damper has been built using different simulation tools, and a successful comparison with the real footbridge and the real damper has been carried out. This simulated model has allowed the reproduction of the behaviour of the footbridge and damper when a pedestrian walks across the footbridge. Once it is determined that the simulation results are similar to real data, the control system is introduced into the model. In this sense, different strategies based on Neuro Fuzzy systems have been studied. In fact, an ANFIS (Artificial Neuro Fuzzy Inference System) method has also been used, in addition to an alternative Neuro Fuzzy approach. Several trials have been carried out, using both techniques, obtaining satisfactory results after using these techniques.

Keywords

References

  1. Casado, C.M., de Sebastian, J., Poncela, A.V., Lorenzana, A., (2008), "Design of a semi-active hmed mass damper for the science museum footbridge of Valladolid", Proceedings of the 4th European Conference on Structural Control, ISBN: 978-5-904045-10-4.
  2. Casado, C.M., Carlos, M., Diaz, I.M., de Sebastian, J., Poncela, A.V. and Lorenzana, A. (2013), "Implementation of passive and active vibration control on an in-service footbridge", Struct. Control Health Monit., 20( 1), 70-87. https://doi.org/10.1002/stc.471
  3. Dong, X.M., Yu, M., Liao, C.R. and Chen, W.M. (2010), "Comparative research on semi-active control strategies for magneto-rheological suspension", Nonlinear Dynam., 59(3), 433-453. https://doi.org/10.1007/s11071-009-9550-8
  4. Gomez, M. (2004), "A new and unusual cable-stayed footbridge at Valladolid (Spain)", Proceedings of the Steelbridge 2004: Symposium International sur les Ponts Metalliques, Milau, France, 23-25 June, 2004.
  5. Haibo, L. and Jianwei, Y. (2009), "Study on semi-active suspension system simulation based on magnetorheological damper", Proceedings of the 2nd International Conference on Intelligent Computation Technology and Automation.
  6. Jang, J.S.R. (1993), "ANFIS: Adaptive-Network-based Fuzzy Inference Systems", IEEE T. Syst., Man, Cybernetics, 23, 665-685. https://doi.org/10.1109/21.256541
  7. Jansen, L.M. and Dyke, S.J. (1999), "Semi-active control strategies for MR dampers: a comparative study" , Am. Soc. Civil Eng., J. Eng. Mech., 126(8), 795-803.
  8. Ji, H.R., Moon, Y.J., Kim, C.H. and Lee, I.W. (2005), "Structural vibration control using semiactive tuned mass damper", Proceedings of the 18th KKCNN Symposium on Civil Engineering-KAIST6.
  9. Marichal, G., Acosta, L., Moreno, L., Mendez, J., Rodrigo, J. and Sigut, M. (2001), "Obstacle avoidance for a mobile robot: A neuro-fuzzy approach", Fuzzy Set. Syst., 124(2), 171-179. https://doi.org/10.1016/S0165-0114(00)00095-6
  10. Marichal, G.N, Hernandez, A., Acosta, L. and Gonzalez, E.J. (2009), "A neuro-fuzzy system for extracting environment features based on ultrasonic sensors", Sensors, 9(12), 10023-10043. https://doi.org/10.3390/s91210023
  11. Marichal, G., Artes, M., Garca Prada, J. and Casanova, O. (2011), "Extraction of rules for faulty bearing classification by a neuro-fuzzy approach", Mech. Syst. Signal Pr., 25, 2073-2082. https://doi.org/10.1016/j.ymssp.2011.01.014
  12. Miller, L.R. (1988), "Tuning passive semi-active, and fully active suspension systems", Proceedings of the 27th Conference on Decision and Control, Austin, TX.
  13. Poncela, A. and Schmitendorf, W. (1998), "Design of a tuned mass damper for seismic excited building via H-infinity output feedback control", Proceedings of the 1998 IEEE International Conference on Control Applications.
  14. Ramallo, J.C., Yoshioka, H. and Spencer, B.F. (2004), "A two-step identification technique for semiactive control systems", Struct. Control Health Monit., 11, 273-289. https://doi.org/10.1002/stc.43
  15. Simulink (R) Available online http://www.mathworks.com/products/simulink/
  16. Spencer, B.F., Dyke, S.J., Sain, M.K. and Carlson, J.D. (1997), "Phenomenological model of a magnetorheological damper", J. Eng. Mech. - ASCE, 123(3), 230-238. https://doi.org/10.1061/(ASCE)0733-9399(1997)123:3(230)
  17. Widrow, B., de Claris, N. and Kalman, E. (1971), Adaptive filters, Aspects of Network and System Theory, Holt, Rinehart, and Winston
  18. Yoshioka, H., Ramallo, J.C. and Spencer, B.F. (2002), "Smart base isolation strategies employing magnetorheological dampers", J. Eng. Mech. - ASCE, 128(5), 540-551. https://doi.org/10.1061/(ASCE)0733-9399(2002)128:5(540)
  19. Zivanovic, S., Pavic, A. and Reynolds, P. (2005), "Vibration serviceability of footbridges under human-induced excitation: A literature review", J. Sound Vib., 279(1), 1-74. https://doi.org/10.1016/j.jsv.2004.01.019

Cited by

  1. Intelligent control of an MR prosthesis knee using of a hybrid self-organizing fuzzy controller and multidimensional wavelet NN vol.31, pp.7, 2017, https://doi.org/10.1007/s12206-016-1236-9
  2. The Risk Assessment of Tunnels Based on Grey Correlation and Entropy Weight Method 2018, https://doi.org/10.1007/s10706-017-0415-5
  3. Stochastic vibration suppression analysis of an optimal bounded controlled sandwich beam with MR visco-elastomer core vol.19, pp.1, 2015, https://doi.org/10.12989/sss.2017.19.1.021
  4. Stochastic vibration response of a sandwich beam with nonlinear adjustable visco-elastomer core and supported mass vol.64, pp.2, 2017, https://doi.org/10.12989/sem.2017.64.2.259