Nowadays, vibration control of structures is considered as a challenging field among scientists and engineers. Structural damage and financial losses due to recent earthquakes in different countries have more than ever before accentuated the importance of controlling earthquake-induced vibrations. In recent years, semi-active control has been introduced as an efficient and reliable type of structural control which provides the reliability of passive control and flexibility of active control systems at the same time. In this study, the performance of a semi-active tuned mass damper (TMD) with adaptive magnetorheological (MR) damper is investigated using type-1 and -2 fuzzy controllers for seismic vibration mitigation of an 11-degree of freedom building model. The TMD is installed on the roof and the MR damper is located on the 11th story. The MR damper has a capacity of producing a 1000 kN control force. The fuzzy system is designed based on the acceleration and velocity of the top floor determining the input voltage needed to produce the control force based on accelerating or decelerating movements of structure. The seismic performance of semi-active type-2 controller, which considers the uncertainties related to input variables, is higher than that of the type-1 fuzzy controller. The type-2 fuzzy controller is capable of reducing further the maximum displacement, acceleration, and base shear of the structure by 11.7, 14, and 11.2%, respectively, compared to the type-1 fuzzy controller.
AbeMFujinoY (1994) Dynamic characterization of multiple tuned mass dampers and some design formulas. Earthquake Engineering & Structural Dynamics23(8): 813–835.
2.
AnkireddiSYangHTY (1996) Simple ATMD control methodology for tall buildings subject to wind loads. Journal of Structural Engineering122(1): 83–91.
3.
ChangJCSoongTT (1980) Structural control using active tuned mass dampers. Journal of the Engineering Mechanics Division106(6): 1091–1098.
4.
DykeSJCaicedoJMTuranGet al. (2003) Phase I benchmark control problem for seismic response of cable-stayed bridges. Journal of Structural Engineering129(7): 857–872.
5.
FrahmH (1911) Device for damping vibrations of bodies, Patent 989: 958, USA.
6.
HagrasHA (2004) A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots. IEEE Transactions on Fuzzy Systems12(4): 524–539.
7.
Innocent PR, John RI, Belton I, et al. (2001) Type 2 fuzzy representations of lung scans to predict pulmonary emboli. In: Joint 9th IFSA world congress and 20th NAFIPS international conference, Vancouver, BC, 25–28 July 2001, pp.1902–1907. Vancouver, BC, Canada: IEEE.
8.
JohnRIInnocentPRBarnesMR (2000) Neuro-fuzzy clustering of radiographic tibia image data using type 2 fuzzy sets. Information Sciences125(1): 65–82.
9.
JungBHRuangrassameeAKawashimaKet al. (2002) Seismic protection of nonlinear coupled bridge systems using semi-active control strategy. KSCE Journal of Civil Engineering: Structural Engineering6(1): 47–60.
10.
JungHJSpencerBFJrLeeIW (2003) Control of seismically excited cable-stayed bridge employing magnetorheological fluid dampers. Journal of Structural Engineering129(7): 873–883.
11.
KimHSKangJW (2012) Semi-active fuzzy control of a wind-excited tall building using multi-objective genetic algorithm. Engineering Structures41: 242–257.
12.
KimHSChangCKangJW (2015) Control performance evaluation of semi-active TMD subjected to various types of loads. International Journal of Steel Structures15(3): 581–594.
13.
LiC (2000) Performance of multiple tuned mass dampers for attenuating undesirable oscillations of structures under the ground acceleration. Earthquake Engineering & Structural Dynamics29(9): 1405–1421.
14.
LiCQuW (2006) Optimum properties of multiple tuned mass dampers for reduction of translational and torsional response of structures subject to ground acceleration. Engineering Structures28(4): 472–494.
15.
LiangQMendelJM (2000) Equalization of nonlinear time-varying channels using type-2 fuzzy adaptive filters. IEEE Transactions on Fuzzy Systems8(5): 551–563.
16.
LiangQMendelJM (2001) MPEG VBR video traffic modeling and classification using fuzzy technique. IEEE Transactions on Fuzzy Systems9(1): 183–193.
17.
LiangQKarnikNNMendelJM (2000) Connection admission control in ATM networks using survey-based type-2 fuzzy logic systems. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews30(3): 329–339.
18.
Liu Y, Gordaninejad F, Evrensel CA, et al. (2000) Semiactive control of a two-span bridge using field-controllable magneto-rheological dampers. In SPIE’s 7th annual international symposium on smart structures and materials, Location?, 20 April 2000, pp.199–206. Newport Beach, California: International Society for Optics and Photonics.
19.
LiuYGordaninejadFEvrenselCAet al. (2005) Comparative study on vibration control of a scaled bridge using fail-safe magneto-rheological fluid dampers. Journal of Structural Engineering131(5): 743–751.
20.
OkSYKimDSParkKSet al. (2007) Semi-active fuzzy control of cable-stayed bridges using magneto-rheological dampers. Engineering Structures29(5): 776–788.
21.
PastiaCLucaSG (2013) Vibration control of a frame structure using semi-active tuned mass damper. Buletinul Institutului Politehnic din lasi. Sectia Constructii, Arhitectura59(4): 31.
22.
PourzeynaliSLavasaniHHModarayiAH (2007) Active control of high rise building structures using fuzzy logic and genetic algorithms. Engineering Structures29(3): 346–357.
23.
RenziESerinoG (2004) Testing and modelling a semi‐actively controlled steel frame structure equipped with MR dampers. Structural Control and Health Monitoring11(3): 189–221.
24.
ShariatmadarHGolnargesiS (2015) Structural control with active tuned mass damper by type 2 fuzzy logic controller for seismic excitations. Sharif Journal of Civil Engineering31(2): 21–32.
25.
ShariatmadarHGolnargesiSAkbarzadeh-TbMR (2014) Vibration control of buildings using ATMD against earthquake excitations through interval type-2 fuzzy logic controller. Asian Journal of Civil Engineering (BHRC)15(3): 321–338.
26.
SodeyamaHSunakodaKFujitaniHet al. (2003) Dynamic tests and simulation of magneto-rheological dampers. Computer‐Aided Civil and Infrastructure Engineering18(1): 45–57.
27.
SpencerBFJrNagarajaiahS (2003) State of the art of structural control. Journal of Structural Engineering129(7): 845–856.
28.
Spencer BF, Dyke SJ, Sain MK, et al. (1996) Nonlinear identification of semi-active control devices. In: Engineering Mechanics. ASCE, pp.164–167.
29.
WarburtonGB (1982) Optimum absorber parameters for various combinations of response and excitation parameters. Earthquake Engineering & Structural Dynamics10(3): 381–401.
30.
WuDMendelJM (2007) Uncertainty measures for interval type-2 fuzzy sets. Information Sciences177(23): 5378–5393.
31.
XuYLChenJNgCLet al. (2005) Semi-active seismic response control of buildings with podium structure. Journal of Structural Engineering131(6): 890–899.
32.
XuZDShenYPGuoYQ (2003) Semi-active control of structures incorporated with magnetorheological dampers using neural networks. Smart Materials and Structures12(1): 80.
33.
YanGZhouLL (2006) Integrated fuzzy logic and genetic algorithms for multi-objective control of structures using MR dampers. Journal of Sound and Vibration296(1): 368–382.
34.
YoshidaODykeSJ (2005) Response control of full-scale irregular buildings using magnetorheological dampers. Journal of Structural Engineering131(5): 734–742.
35.
ZahraiSMSalehiH (2014) Semi-active seismic control of mid-rise structures using magneto-rheological dampers and two proposed improving mechanisms. Iranian Journal of Science and Technology: Transactions of Civil Engineering38(C1): 21–36.
36.
Ze-bingDAIHuangJWangH (2004) Semi-active control of a cable-stayed bridge under multiple-support excitations. Journal of Zhejiang University: Science A5(3): 317–325.
