Please wait a minute...
Frontiers of Structural and Civil Engineering

ISSN 2095-2430

ISSN 2095-2449(Online)

CN 10-1023/X

Postal Subscription Code 80-968

2018 Impact Factor: 1.272

Front. Struct. Civ. Eng.    2020, Vol. 14 Issue (3) : 706-721    https://doi.org/10.1007/s11709-020-0612-9
RESEARCH ARTICLE
Semi-active fuzzy control of Lali Cable-Stayed Bridge using MR dampers under seismic excitation
Sajad JAVADINASAB HORMOZABAD, Amir K. GHORBANI-TANHA()
School of Civil Engineering, College of Engineering, University of Tehran, Tehran 11155-4563, Iran
 Download: PDF(2955 KB)   HTML
 Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Abstract

Seismic control of cable-stayed bridges is of paramount importance due to their complex dynamic behavior, high flexibility, and low structural damping. In the present study, several semi-active Fuzzy Control Algorithms (FCAs) for vibration mitigation of Lali Cable-Stayed Bridge are devised. To demonstrate the efficiency of the algorithms, a comprehensive nonlinear 3-D model of the bridge is created using OpenSees. An efficient method for connecting MATLAB and OpenSees is devised for applying FCAs to the structural model of the bridge. Two innovative fuzzy rule-bases are introduced. A total of six different fuzzy rule-bases are utilized. The efficiency of the FCAs is evaluated in a comparative manner. The performance of fuzzy control systems is also compared with a sky-hook and a passive-on system. Moreover, the sensitivity of efficiency of control systems to the peak ground acceleration is evaluated qualitatively. In addition, the effect of time lag is also investigated. This study thoroughly examines the efficiency of the FCAs in different aspects. Therefore, the results can be regarded as a general guide to design semi-active fuzzy control systems for vibration mitigation of cable-stayed bridges.

Keywords semi-active control      Fuzzy Control Algorithm      cable-stayed bridge      MR damper      Lali Bridge     
Corresponding Author(s): Amir K. GHORBANI-TANHA   
Just Accepted Date: 07 May 2020   Online First Date: 16 June 2020    Issue Date: 13 July 2020
 Cite this article:   
Sajad JAVADINASAB HORMOZABAD,Amir K. GHORBANI-TANHA. Semi-active fuzzy control of Lali Cable-Stayed Bridge using MR dampers under seismic excitation[J]. Front. Struct. Civ. Eng., 2020, 14(3): 706-721.
 URL:  
https://academic.hep.com.cn/fsce/EN/10.1007/s11709-020-0612-9
https://academic.hep.com.cn/fsce/EN/Y2020/V14/I3/706
Fig.1  Overall layout of the Lali Bridge (dimensions in m).
Fig.2  Pier, pylon, and deck sections of the Lali Bridge.
Fig.3  Finite element model of the Lali Bridge: (a) overall view of the SAP2000 model; (b) mechanical behavior of tension-only material used for cables in OpenSees model.
parameter element value
yielding strength of steel deck beams 360 MPa (ST52)
elastic modulus of steel deck beams 2.1E5 MPa
yielding strength of steel cables 1000 MPa
elastic modulus of steel cables 1.95E5 MPa
compressive strength of concrete deck slabs 45 MPa
compressive strength of concrete piers 40 MPa
yielding strength of steel reinforcement piers 400 MPa (S400)
Tab.1  General characteristics of the finite element model of the bridge
parameter value
αa 1.0872×105 N/cm
αb 4.9616×105 N/cm/V
C0a 4.40 N s/cm
C0b 44.0 N s/cm/V
Am 1.2
n 1
β 3 cm−1
γ 3 cm−1
η 50 s−1
Tab.2  Parameters used for simulating the MR dampers
Fig.4  The (a) first, (b) second, (c) third, (d) fourth, (e) fifth, and (f) sixth mode shapes of the Lali Bridge.
Fig.5  Verification of the displacement response of the middle point of the deck subjected to (a) El Centro and (b) Northridge earthquake; (c) verification of the vertical displacements of the deck due to cable prestress forces.
record type Earthquake Station PGA
near-field Kobe, 1995 KJM 0.83g
Northridge, 1994 Sylmar-Olive 0.84g
Tabas, 1978 Tabas 0.85g
Chi Chi, 1999 TCU065 0.83g
far-field Imperial Valley, 1940 El Centro 0.35g
Tokachi_Oki, 1968 Hachinohe 0.23g
Tabas, 1978 Ferdows 0.11g
Loma Prieta, 1989 Richmond City Hall 0.12g
Tab.3  Characteristics of the ground motion records
Fig.6  (a) Schematic model of the MR damper; (b) hysteretic behavior of the MR damper for various values of input voltage.
Fig.7  Schematic arrangement of MR dampers and measurement sensors.
Fig.8  Membership functions for (a) input variables used in rule base 1, 3, 4, and 5; (b) input variables used in rule base 2 and 3; (c) input variables used in rule base 2 and 6; (d) output variables (units are in SI).
VelRel
NVL NL NM NS NVS ZO PVS PS PM PL PVL
VL L M S VS ZO VS S M L VL
Tab.4  Fuzzy rule table for RB1
Disp
NVL NL NM NS NVS ZO PVS PS PM PL PVL
VelRel P ZO ZO ZO ZO ZO VL VL VL VL VL VL
N VL VL VL VL VL VL ZO ZO ZO ZO ZO
Tab.5  Fuzzy rule table for RB2
Disp
NVL NL NM NS NVS ZO PVS PS PM PL PVL
VelRel PVL L VL VL VL VL VL VL VL VL VL VL
PL M L VL VL VL VL VL VL VL VL VL
PM S M L VL VL VL VL VL VL VL VL
PS VS S M L VL VL VL VL VL VL VL
PVS ZO VS S M L VL VL VL VL VL VL
ZO VL VL VL VL VL VL VL VL VL VL VL
NVS VL VL VL VL VL VL L M S VS ZO
NS VL VL VL VL VL VL VL L M S VS
NM VL VL VL VL VL VL VL VL L M S
NL VL VL VL VL VL VL VL VL VL L M
NVL VL VL VL VL VL VL VL VL VL VL L
Tab.6  Fuzzy rule table for RB3
VelRel
NVL NL NM NS NVS ZO PVS PS PM PL PVL
ZO VS S M L VL L M S VS ZO
Tab.7  Fuzzy rule table for RB4
Vel
NVL NL NM NS NVS ZO PVS PS PM PL PVL
VelRel PVL ZO ZO ZO ZO ZO ZO VS S M L VL
PL ZO ZO ZO ZO ZO VS S M L VL VL
PM ZO ZO ZO ZO ZO S M L VL VL VL
PS ZO ZO ZO ZO ZO M L VL VL VL VL
PVS ZO ZO ZO ZO ZO L VL VL VL VL VL
ZO VL VL VL VL VL VL VL VL VL VL VL
NVS VL VL VL VL VL L ZO ZO ZO ZO ZO
NS VL VL VL VL L M ZO ZO ZO ZO ZO
NM VL VL VL L M S ZO ZO ZO ZO ZO
NL VL VL L M S VS ZO ZO ZO ZO ZO
NVL VL L M S VS ZO ZO ZO ZO ZO ZO
Tab.8  Fuzzy rule table for RB5
Vel
NVL NL NM NS NVS ZO PVS PS PM PL PVL
VelRel P ZO ZO ZO ZO ZO VL VL VL VL VL VL
N VL VL VL VL VL VL ZO ZO ZO ZO ZO
Tab.9  Fuzzy rule tables for RB6
control system J1 J2 J3 J4 J5 J6 J7 J8 J9 J10
FIS1 0.630 0.889 0.969 0.919 0.931 0.430 0.645 0.570 0.448 0.993
FIS2 0.739 1.072 1.057 1.166 0.992 0.538 0.779 0.897 0.714 0.999
FIS3 0.648 0.965 1.014 1.034 0.972 0.400 0.737 0.706 0.614 0.995
FIS4 0.698 0.981 1.002 1.065 0.967 0.506 0.749 0.734 0.576 0.995
FIS5 0.465 1.016 0.992 1.001 0.985 0.325 0.668 0.674 0.454 0.998
FIS6 0.433 1.011 0.998 1.006 1.000 0.290 0.726 0.734 0.495 0.999
sky-hook 0.420 1.048 1.020 1.028 1.016 0.233 0.956 0.906 0.751 0.999
passive 0.575 0.969 0.957 0.966 0.956 0.361 0.775 0.637 0.488 0.995
Tab.10  Average performance criteria for control systems subjected to scaled earthquake records
qualitative efficiency overall ranking
FIS1 F E E E E F E E E E 5
FIS2 P P P P F P G P P P 8
FIS3 F G G G G G VG G G VG 6
FIS4 P G G G G P VG G G VG 7
FIS5 E F VG VG F VG E VG E F 2
FIS6 E F G VG P E VG G E P 1
sky-hook E P F G P E P P P P 3
Passive G G E E VG G G E E VG 4
Tab.11  Overall Qualitative Evaluation of Efficiency of Control Systems
criterion J1 J2 J3 J4 J5 J6 J7 J8 J9 J10
relative importance 10.0 0.2 2.0 2.0 2.0 10.0 4.0 2.0 2.0 0.2
Tab.12  Relative importance of each criterion considered for the overall evaluation
?control system average slope sensitivity of efficiency to PGA
FIS1 0.128 very stable
FIS2 0.338 very sensitive
FIS3 0.319 very sensitive
FIS4 0.341 very sensitive
FIS5 0.256 sensitive
FIS6 0.325 very sensitive
sky-hook 0.346 very sensitive
passive 0.284 sensitive
Tab.13  Evaluation of sensitivity of control systems to PGA
criterion average slope variation of control systems efficiency due to increase in PGA
J1 0.403 very significant decrease
J2 −0.440??? very significant increase
J3 0.121 moderate decrease
J4 0.435 very significant decrease
J5 0.070 no meaningful change
J6 0.215 significant decrease
J7 −0.114??? moderate increase
J8 0.302 very significant decrease
J9 0.353 very significant decrease
J10 −0.002??? no meaningful change
Tab.14  Evaluation of sensitivity of performance criteria to PGA
control system relative error (%)
J1 J2 J3 J4 J5 J6 J7 J8 J9 J10 average
FIS1 ?3.77 ??7.02 2.23 6.99 0.16 11.82 150.98 7.30 ?8.81 0.02 19.91
FIS2 18.91 148.06 1.42 −2.11?? 0.10 43.10 485.77 24.32? 43.63 0.11 76.33
FIS3 11.24 167.74 1.09 −0.76?? 0.45 36.32 642.47 7.32 10.55 0.04 87.65
FIS4 ?9.30 ?83.98 2.75 −1.32?? −1.56?? 35.74 321.68 6.36 ?9.68 −0.01?? 46.66
FIS5 25.63 142.16 7.17 1.86 3.99 39.54 598.95 6.96 11.05 0.03 83.74
FIS6 26.63 148.53 12.86? 0.23 0.92 46.46 656.11 5.17 ?8.68 0.05 90.57
average 15.91 116.25 4.59 0.82 0.68 35.50 475.99 9.57 15.40 0.04
Tab.15  The average percentage of relative errors due to a 0.1 sec time lag
Fig.9  Variation of J1 vs. PGA for El Centro earthquake.
Fig.10  Evaluation of failure and unseating of cables for (a) FIS1, (b) FIS6 subjected to Northridge record.
1 H W George. Influence of deck material on response of cable-stayed bridges to live loads. Journal of Bridge Engineering, 1999, 4(2): 136–142
https://doi.org/10.1061/(ASCE)1084-0702(1999)4:2(136)
2 A B Mehrabi. In-service evaluation of cable-stayed bridges, overview of available methods and findings. Journal of Bridge Engineering, 2006, 11(6): 716–724
https://doi.org/10.1061/(ASCE)1084-0702(2006)11:6(716)
3 M Hasan, E Khalil, W Attia, A Turkey. Influence of deck longitudinal prestressing on cable-stayed bridges. Structural Engineering International, 2015, 25(3): 292–299
4 J M Caicedo, S J Dyke, S J Moon, L A Bergman, G Turan, S Hague. Phase II benchmark control problem for seismic response of cable-stayed bridges. Structural Control and Health Monitoring, 2003, 10(3–4): 137–168
https://doi.org/10.1002/stc.23
5 N A Nariman. A novel structural modification to eliminate the early coupling between bending and torsional mode shapes in a cable-stayed bridge. Frontiers of Structural and Civil Engineering, 2017, 11(2): 131–142
https://doi.org/10.1007/s11709-016-0376-4
6 A M Abdel-Ghaffar. Cable-stayed bridges under seismic action. In: Proceedings of the Seminar Cable-Stayed Bridges: Recent DevelOpment and Their Future. Yokohama, 1991
7 G Housner, L A Bergman, T K Caughey, A G Chassiakos, R O Claus, S F Masri, R E Skelton, T T Soong, B F Spencer, J T Yao. Structural control: Past, present, and future. Journal of Engineering Mechanics, 1997, 123(9): 897–971
https://doi.org/10.1061/(ASCE)0733-9399(1997)123:9(897)
8 M D Symans, M C Constantinou. Semi-active control systems for seismic protection of structures: A state-of-the-art review. Engineering Structures, 1999, 21(6): 469–487
https://doi.org/10.1016/S0141-0296(97)00225-3
9 Y Fujino. Vibration, control and monitoring of long-span bridges —Recent research, developments and practice in Japan. Journal of Constructional Steel Research, 2002, 58(1): 71–97
https://doi.org/10.1016/S0143-974X(01)00049-9
10 B F Spencer Jr, S Nagarajaiah. State of the art of structural control. Journal of Structural Engineering, 2003, 129(7): 845–856
https://doi.org/10.1061/(ASCE)0733-9445(2003)129:7(845)
11 S Javadinasab Hormozabad, M Ramezani, A K Ghorbani-Tanha. Seismic behavior and vibration control of Lali Cable-Stayed Bridge using TMD. In: Proceedings of the 4th International Conference on Bridge (4IBC2015). Tehran, 2015
12 B F Spencer Jr, S J Dyke, M K Sain, J Carlson. Phenomenological model for magnetorheological dampers. Journal of Engineering Mechanics, 1997, 123(3): 230–238
https://doi.org/10.1061/(ASCE)0733-9399(1997)123:3(230)
13 W L He, A K Agrawal, K Mahmoud. Control of seismically excited cable-stayed bridge using resetting semiactive stiffness dampers. Journal of Bridge Engineering, 2001, 6(6): 376–384
https://doi.org/10.1061/(ASCE)1084-0702(2001)6:6(376)
14 M Bitaraf, O E Ozbulut, S Hurlebaus, L Barroso. Application of semi-active control strategies for seismic protection of buildings with MR dampers. Engineering Structures, 2010, 32(10): 3040–3047
https://doi.org/10.1016/j.engstruct.2010.05.023
15 O El-Khoury, C Kim, A Shafieezadeh, J E Hur, G H Heo. Experimental study of the semi-active control of a nonlinear two-span bridge using stochastic optimal polynomial control. Smart Materials and Structures, 2015, 24(6): 065011
https://doi.org/10.1088/0964-1726/24/6/065011
16 M S Miah, E N Chatzi, V K Dertimanis, F Weber. Real-time experimental validation of a novel semi-active control scheme for vibration mitigation. Structural Control and Health Monitoring, 2017, 24(3): e1878
https://doi.org/10.1002/stc.1878
17 S Javadinasab Hormozabad, S M Zahrai. Innovative adaptive viscous damper to improve seismic control of structures. Journal of Vibration and Control, 2019, 25(12): 1833–1851
https://doi.org/10.1177/1077546319841763
18 S J Dyke, J M Caicedo, G Turan, L A Bergman, S Hague. Phase I benchmark control problem for seismic response of cable-stayed bridges. Journal of Structural Engineering, 2003, 129(7): 857–872
https://doi.org/10.1061/(ASCE)0733-9445(2003)129:7(857)
19 H Iemura, M H Pradono. Application of pseudo-negative stiffness control to the benchmark cable-stayed bridge. Structural Control and Health Monitoring, 2003, 10(3–4): 187–203
https://doi.org/10.1002/stc.25
20 J N Yang, S Lin, F Jabbari. H2-based control strategies for civil engineering structures. Structural Control and Health Monitoring, 2003, 10(3–4): 205–230
https://doi.org/10.1002/stc.26
21 A K Agrawal, J N Yang, W L He. Applications of some semiactive control systems to benchmark cable-stayed bridge. Journal of Structural Engineering, 2003, 129(7): 884–894
https://doi.org/10.1061/(ASCE)0733-9445(2003)129:7(884)
22 S J Dyke, B F Spencer Jr, M K Sain, J D Carlson. Modeling and control of magnetorheological dampers for seismic response reduction. Smart Materials and Structures, 1996, 5(5): 565–575
https://doi.org/10.1088/0964-1726/5/5/006
23 L M Jansen, S J Dyke. Semiactive control strategies for MR dampers: Comparative study. Journal of Engineering Mechanics, 2000, 126(8): 795–803
https://doi.org/10.1061/(ASCE)0733-9399(2000)126:8(795)
24 F Yi, S J Dyke, J M Caicedo, J D Carlson. Experimental verification of multi-input seismic control strategies for smart dampers. Journal of Engineering Mechanics, 2001, 127(11): 1152–1164
https://doi.org/10.1061/(ASCE)0733-9399(2001)127:11(1152)
25 J C Ramallo, E A Johnson, B F Spencer Jr. “Smart” base isolation systems. Journal of Engineering Mechanics, 2002, 128(10): 1088–1099
https://doi.org/10.1061/(ASCE)0733-9399(2002)128:10(1088)
26 L H Xu, Z X Li. Semi-active multi-step predictive control of structures using MR dampers. Earthquake Engineering & Structural Dynamics, 2008, 37(12): 1435–1448
https://doi.org/10.1002/eqe.822
27 H J Jung, B F Spencer Jr, I W Lee. Control of seismically excited cable-stayed bridge employing magnetorheological fluid dampers. Journal of Structural Engineering, 2003, 129(7): 873–883
https://doi.org/10.1061/(ASCE)0733-9445(2003)129:7(873)
28 M D Symans, S W Kelly. Fuzzy logic control of bridge structures using intelligent semi-active seismic isolation systems. Earthquake Engineering & Structural Dynamics, 1999, 28(1): 37–60
https://doi.org/10.1002/(SICI)1096-9845(199901)28:1<37::AID-EQE803>3.0.CO;2-Z
29 K S Park, H M Koh, S Y Ok, C W Seo. Fuzzy supervisory control of earthquake-excited cable-stayed bridges. Engineering Structures, 2005, 27(7): 1086–1100
https://doi.org/10.1016/j.engstruct.2005.02.007
30 S Y Ok, D S Kim, K S Park, H M Koh. Semi-active fuzzy control of cable-stayed bridges using magneto-rheological dampers. Engineering Structures, 2007, 29(5): 776–788
https://doi.org/10.1016/j.engstruct.2006.06.020
31 H Yoshioka, J C Ramallo, B F Spencer Jr. “Smart” base isolation strategies employing magnetorheological dampers. Journal of Engineering Mechanics, 2002, 128(5): 540–551
https://doi.org/10.1061/(ASCE)0733-9399(2002)128:5(540)
32 E A Johnson, G A Baker, B F Spencer Jr, Y Fujino. Semiactive damping of stay cables. Journal of Engineering Mechanics, 2007, 133(1): 1–11
https://doi.org/10.1061/(ASCE)0733-9399(2007)133:1(1)
33 S Salari, S Javadinasab Hormozabad, A K Ghorbani-Tanha, M Rahimian. Innovative mobile TMD system for semi-active vibration control of inclined sagged cables. KSCE Journal of Civil Engineering, 2019, 23(2): 641–653
https://doi.org/10.1007/s12205-018-0161-0
34 A Ghahramani. Static and dynamic analysis of Lali bridge basin and caisson foundation. In: Proceedings of the 8th International Congress on Civil Engineering. Shiraz, 2009
35 MATLAB. Fuzzy Logic ToolboxTM User’s Guide. Natick, MA: The Math Works, Inc., 2011
[1] Khaled ZIZOUNI, Leyla FALI, Younes SADEK, Ismail Khalil BOUSSERHANE. Neural network control for earthquake structural vibration reduction using MRD[J]. Front. Struct. Civ. Eng., 2019, 13(5): 1171-1182.
[2] Yan XU, Shijie ZENG, Xinzhi DUAN, Dongbing JI. Seismic experimental study on a concrete pylon from a typical medium span cable-stayed bridge[J]. Front. Struct. Civ. Eng., 2018, 12(3): 401-411.
[3] Yundong SHI, Tracy C BECKER, Masahiro KURATA, Masayoshi NAKASHIMA. H control in the frequency domain for a semi-active floor isolation system[J]. Front Struc Civil Eng, 2013, 7(3): 264-275.
[4] Yan XU, Shide HU. Seismic design of high-rise towers for cable-stayed bridges under strong earthquakes[J]. Front Arch Civil Eng Chin, 2011, 5(4): 451-457.
[5] Man-Chung TANG. Design concept of the Twin River Bridges in Chongqing, China[J]. Front Arch Civil Eng Chin, 2011, 5(4): 427-431.
[6] Yong XIA, Jing ZHANG, Youlin XU, Yozo FUJINO, . Parametric oscillation of cables and aerodynamic effect[J]. Front. Struct. Civ. Eng., 2010, 4(3): 321-325.
[7] ZHU Jinsong, XIAO Rucheng. Damage identification of a large-span concrete cable-stayed bridge based on genetic algorithm[J]. Front. Struct. Civ. Eng., 2007, 1(2): 170-175.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed