Browse > Article
http://dx.doi.org/10.12989/sem.2012.41.3.349

Effects of multiple MR dampers controlled by fuzzy-based strategies on structural vibration reduction  

Wilson, Claudia Mara Dias (New Mexico Institute of Mining and Technology)
Publication Information
Structural Engineering and Mechanics / v.41, no.3, 2012 , pp. 349-363 More about this Journal
Abstract
Fuzzy logic based control has recently been proposed for regulating the properties of magnetorheological (MR) dampers in an effort to reduce vibrations of structures subjected to seismic excitations. So far, most studies showing the effectiveness of these algorithms have focused on the use of a single MR damper. Because multiple dampers would be needed in practical applications, this study aims to evaluate the effects of multiple individually tuned fuzzy-controlled MR dampers in reducing responses of a multi-degree-of-freedom structure subjected to seismic motions. Two different fuzzy-control algorithms are considered, a traditional controller where all parameters are kept constant, and a gain-scheduling control strategy. Different damper placement configurations are also considered, as are different numbers of MR dampers. To determine the robustness of the fuzzy controllers developed to changes in ground excitation, the structure selected is subjected to different earthquake records. Responses analyzed include peak and root mean square displacements, accelerations, and interstory drifts. Results obtained with the fuzzy-based control schemes are compared to passive control strategies.
Keywords
MR damper; semi-active control; fuzzy logic; fuzzy control; structural control;
Citations & Related Records
 (Related Records In Web of Science)
연도 인용수 순위
  • Reference
1 Ali, S.F. and Ramaswamy, A. (2009), "Optimal fuzzy logic control for MDOF structural systems using evolutionary algorithms", Eng. Appl. Artif. Int., 22, 407-419.   DOI   ScienceOn
2 Chao, C.T. and Teng, C.C. (1997), "A PD-like self-tuning fuzzy controller without steady-state error", Fuzzy Set. Syst., 87, 141-154.   DOI   ScienceOn
3 Choi, K.M., Cho, S.W., Jung, H.J. and Lee, I.W. (2004), "Semi-active fuzzy control for seismic response reduction using magnetorheological dampers", Earthq. Eng. Struch., 33, 723-736.   DOI   ScienceOn
4 Dalei, G. and Jianqiang, Y. (2002), "Semi-active seismic isolation control based on MR damper and neural networks", Proceedings of 6th Intern. Conf. on Motion and Vibration Control, Saitama, Japan.
5 Driankov, D., Hellendoorn, H. and Reinfrank, M. (1993), An Introduction to Fuzzy Contro., Heidelberg: Springer, Berlin, Germany.
6 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.   DOI   ScienceOn
7 Dyke, S.J. and Spencer Jr., B.F. (1997), "Comparison of semi-active control strategies for the MR damper", Proceedings of Intern. Conf. on Intelligent Information Systems, The Bahamas.
8 Faravelli, L, and Yao, T. (1996), "Use of adaptive networks in fuzzy control of civil structures", Microcomput. Civil Eng., 11, 67-76.   DOI
9 Hiemenz, G.J., Choi, Y.T. and Wereley, N.M. (2000), "Seismic control of civil structures utilizing semi-active MR bracing systems", Proceeding of Smart Systems for Bridges, Structures, and Highways Conf., Newport Beach, USA.
10 Jing, C., Youlin, X., Weilian, Q. and Zhilun, W. (2004), "Seismic response control of a complex structure using multiple MR dampers: experimental investigation", Earthq. Eng. Eng. Vib., 3(2), 181-193.   DOI   ScienceOn
11 Li, H.X. and Gatland, H.B. (1996), "Conventional fuzzy control and its enhancement", IEEE T. Syst. Man. Cy., 26(5), 791-797.   DOI   ScienceOn
12 Liu, Y., Gordaninejad, F., Evrensel, C.A. and Hitchcock, G. (2001), "An experimental study on fuzzy logic vibration control of a bridge using fail-safe magneto-rheological fluid dampers", Proceedings of Smart Systems and Materials Conf., Newport Beach, USA.
13 Lu, K.C., Loh, C.H. and Yang, J.N. (2008), "Building control using MR-dampers: centralized versus decentralized control", Proceedings 11th Intern. Conf. on Engineering, Science, Construction, and Operations in Challenging Environments, Long Beach, USA.
14 MacVicar-Whelan, P.J. (1976), "Fuzzy sets for man-machine interaction", Int. J. Man Mach. Stud., 8, 687-697.   DOI
15 Neelakantan, V.A. and Washington, G.N. (2008), "Vibration control of structural systems using MR dampers and a 'modified' sliding mode control technique", J. Intel. Mat. Syst. Struct., 19(2), 211-224.   DOI
16 Ni, Y.Q., Chen, Y., Ko, J.M. and Cao, D.Q. (2002), "Neuro-control of cable vibration using semi-active magnetorheological dampers", Eng. Struct., 24, 295-307.   DOI   ScienceOn
17 Park, K.S., Koh, H.M. and Ok, S.Y. (2002), "Active control of earthquake excited structures using fuzzy supervisory technique", Adv. Eng. Softw., 33, 761-768.   DOI   ScienceOn
18 Schurter, K.C. and Roschke, P.N. (2001), "Neuro-fuzzy control of structures using acceleration feedback", Smart Mater. Struct., 10(4), 770-779.   DOI   ScienceOn
19 Shook, D.A., Roschke, P.N., Lin, P.Y. and Loh, C.H. (2008), "GA-optimized fuzzy logic control of a large-scale building for seismic loads", Eng. Struct., 30, 436-449.   DOI   ScienceOn
20 Spencer Jr., 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.   DOI   ScienceOn
21 Wilson, C.M.D. (2005), Fuzzy Control of Magnetorheological Dampers for Vibration Reduction of Seismically Excited Structures, Dissertation, Florida State University, Tallahassee, USA.
22 Wilson, C.M.D. and Abdullah, M.M. (2009), "Structural vibration reduction using gain-scheduled fuzzy control of magnetorheological dampers", J. Seismol. Earthq. Eng., 11(2), 97-110.
23 Wilson, C.M.D. and Abdullah, M.M. (2010), "Structural vibration reduction using self-tuning fuzzy control of magnetorheological dampers", B. Earthq. Eng., 8(4), 1037-1054.   DOI   ScienceOn
24 Xu, Y.L., Qu, W.L. and Ko, J.M. (2000), "Seismic response control of frame structures using magnetorheological/electrorheological dampers", Earthq. Eng. Struct., 29, 557-575.   DOI   ScienceOn
25 Xu, Z.D., Shen, Y.P. and Guo, Y.Q. (2003), "Semi-active control of structures incorporated with magnetorheological dampers using neural-networks", Smart Mater. Struct., 12, 80-87.   DOI   ScienceOn
26 Yager, R.R. and Filev, D.P. (1994), Essentials of Fuzzy Modeling and Control, John Wiley and Sons, New York, USA.
27 Yang, G. (2001), "Large-Scale Magnetorheological Fluid Damper for Vibration Mitigation: Modeling, Testing and Control", Dissertation, University of Notre Dame, Notre Dame, USA
28 Yang, G., Spencer Jr., B.F., Carlson, J.D. and Sain, M.K. (2002), "Large-scale MR fluid dampers: mdeling, and dynamic performance considerations", Eng. Struct., 24(3), 309-323.   DOI   ScienceOn
29 Yi, F., Dyke, S.J., Caicedo, J.M. and Carlson, J.D. (2001), "Experimental verification of multi-input seismic control strategies for smart dampers", J. Eng. Mech., 127(11), 1152-1164.   DOI   ScienceOn
30 Zhao, Y. (2001), "Autotuning of an Industrial Weigh Belt Feeder", Dissertation, Florida State University, Tallahassee, USA.
31 Zhao, Y., Collins Jr., E.G. and Dunlap, D. (2003), "Genetic fuzzy parallel parking control for autonomous ground vehicles", Proceedings of American Control Conf., Denver, USA.
32 Zhou, L., Chang, C.C. and Spencer Jr., B.F. (2002), "Intelligent technology-based control of motion and vibration using MR dampers", Earthq. Eng. Eng. Vib., 1(1), 100-110.   DOI