Abstract
An adjustable cuckoo-search wavelet-based fuzzy logic controller (ACSWBFLC) is introduced to mitigate structural responses during seismic motion by using magnetorheological (MR) dampers. The ACSWBFLC incorporates four algorithms: discrete wavelet transform (DWT), fuzzy logic controller (FLC), modified Bouc–Wen model and geometrical nonlinearity algorithm. DWT is applied to acquire the local energy distribution of seismic excitation over the frequency bands. These online data are transmitted to FLC to operate MR damper intelligently based on online excitation frequency. Furthermore, modified Bouc–Wen phenomenological algorithm was utilized to generate the nonlinear behavior of the MR dampers. A wavelet low-pass filter is employed to prevent the stabilization of coefficients and minimize the computational burden. Moreover, geometrical nonlinearities were considered to design a more robust controller. Furthermore, a novel evolutionary algorithm of cuckoo search was used to optimize the placement and the number of MR dampers and sensors in the sense of minimum resultant vibration magnitude. Numerical efforts were considered to validate the efficiency of the proposed FLC. From a designer’s point of view, the proposed ACSWBFLC controller can determine the optimal solutions during a reasonable number of iterations. Finally, numerical examples are utilized to demonstrate the efficiency of ACSWBFLC under several far- and near-fault seismic excitations. The results indicate that ACSWBFLC attenuates the excessive responses of the structural building in real time more efficiently than traditional FLC controllers by using appropriate control force.
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References
Aghajanian S, Baghi H, Amini F, Samani M (2014) Optimal control of steel structures by improved particle swarm. Int J Steel Struct 14:223–230. https://doi.org/10.1007/s13296-014-2003-3
Amezquita-Sanchez JP, Valtierra-Rodriguez M, Aldwaik M, Adeli H (2016) Neurocomputing in civil infrastructure. Sci Iran 23:2417–2428. https://doi.org/10.24200/sci.2016.2301
Amini F, Ghaderi P (2013) Seismic motion control of structures: a developed adaptive backstepping approach. Comput Struct 114–115:18–25. https://doi.org/10.1016/j.compstruc.2012.09.011
Amini F, Zabihi-Samani M (2014) A wavelet-based adaptive pole assignment method for structural control. Comput Aided Civ Infrastruct Eng 29:464–477. https://doi.org/10.1111/mice.12072
Azimi M, Rasoulnia A, Lin Z, Pan H (2017) Improved semi-active control algorithm for hydraulic damper-based braced buildings. Struct Control Health Monit 24:e1991. https://doi.org/10.1002/stc.1991
Basu B, Nagarajaiah S (2008) A wavelet-based time-varying adaptive LQR algorithm for structural control. Eng Struct 30:2470–2477. https://doi.org/10.1016/j.engstruct.2008.01.011
Çetin Ş, Sivrioglu S, Zergeroglu E, Yüksek İ (2011) Semi-active H∞ robust control of six degree of freedom structural system using MR damper. https://doi.org/10.3906/elk-1007-587
Chase JG et al (2006) Re-shaping hysteretic behaviour using semi-active resettable device dampers. Eng Struct 28:1418–1429. https://doi.org/10.1016/j.engstruct.2006.01.011
Daubechies I (1990) The wavelet transform, time–frequency localization and signal analysis. IEEE Trans Inf Theory 36:961–1005
Dyke SJ, Spencer BF Jr, Sain MK, Carlson JD (1996) Modeling and control of magnetorheological dampers for seismic response reduction. Smart Mater Struct 5:565
Gandomi A, Yang X-S, Alavi A (2013) Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems. Eng Comput 29:17–35. https://doi.org/10.1007/s00366-011-0241-y
Ghaderi P, Amini F (2017) Adaptive block backstepping control for civil structures with unknown parameters subjected to seismic excitation. Struct Control Health Monit 24:e1875. https://doi.org/10.1002/stc.1875
Ghanooni-Bagha M, Shayanfar M, Reza-Zadeh O, Zabihi-Samani M (2017) The effect of materials on the reliability of reinforced concrete beams in normal and intense corrosions. Eksploat Niezawodn Maint Reliab 19:393–402. https://doi.org/10.17531/ein.2017.3.10
Hong P, Azimi M, Fei Y, Lin Z (2018) Time–frequency-based data-driven structural diagnosis and damage detection for cable-stayed bridges. J Bridge Eng 23:04018033. https://doi.org/10.1061/(ASCE)BE.1943-5592.0001199
Housner GW et al (1997) Structural control: past, present, and future. J Eng Mech 123:897–971. https://doi.org/10.1061/(ASCE)0733-9399(1997)123:9(897)
Jahani E, Chizari M (2018) Tackling global optimization problems with a novel algorithm–Mouth Brooding Fish algorithm. Appl Soft Comput 62:987–1002. https://doi.org/10.1016/j.asoc.2017.09.035
Kaveh A, Bakhshpoori T, Azimi M (2015) Seismic optimal design of 3D steel frames using cuckoo search algorithm. Struct Des Tall Spec Build 24:210–227. https://doi.org/10.1002/tal.1162
Kim H, Adeli H (2005a) Hybrid control of irregular steel highrise building structures under seismic excitations. Int J Numer Meth Eng 63:1757–1774. https://doi.org/10.1002/nme.1336
Kim H, Adeli H (2005b) Hybrid control of smart structures using a novel wavelet-based algorithm. Comput Aided Civ Infrastruct Eng 20:7–22. https://doi.org/10.1111/j.1467-8667.2005.00373.x
Marzuki K, Rubiyah Y, Majid J, Hazlina S, Mohamad J (2014) Nonlinear identification of a magneto-rheological damper based on dynamic neural networks. Comput Aided Civ Infrastruct Eng 29:221–233. https://doi.org/10.1111/mice.12005
Ok S-Y, Kim D-S, Park K-S, Koh H-M (2007) Semi-active fuzzy control of cable-stayed bridges using magneto-rheological dampers. Eng Struct 29:776–788. https://doi.org/10.1016/j.engstruct.2006.06.020
Rabinow J (1951) Magnetic fluid torque and force transmitting device. 2 1951: 575,360
Sodeyama H, Sunakoda K, Suzuki K, Carlson JD, Spencer BF (2001) A basic study on dynamic characteristics of MR dampers American Society of Mechanical Engineers, Pressure Vessels and Piping Division PVP:115-120
Sodeyama H, Suzuki K, Sunakoda K (2004) Development of Large capacity semi-active seismic damper using magneto-rheological fluid. J Pressure Vessel Technol 126:105–109. https://doi.org/10.1115/1.1634587
Spencer BF, Dyke SJ, Sain MK, Carlson JD (1997) Phenomenological model for magnetorheological dampers. J Eng Mech 123:230–238. https://doi.org/10.1061/(ASCE)0733-9399(1997)123:3(230)
Symans MD, Charney FA, Whittaker AS, Constantinou MC, Kircher CA, Johnson MW, McNamara RJ (2008) Energy dissipation systems for seismic applications: current practice and recent developments. J Struct Eng 134:3–21. https://doi.org/10.1061/(ASCE)0733-9445(2008)134:1(3)
The Mathworks I (2009) MATLAB, Version 7.8.0.347
Tu JW, Liu J, Qu WL, Zhou Q, Cheng HB, Cheng XD (2011) Design and Fabrication of 500-kN large-scale MR damper. J Intell Mater Syst Struct 22:475–487. https://doi.org/10.1177/1045389x11399942
Tusset A, Janzen F, Piccirillo V, Rocha R, Balthazar J, Litak G (2018) On nonlinear dynamics of a parametrically excited pendulum using both active control and passive rotational (MR) damper. J Vib Control 24:1587–1599. https://doi.org/10.1177/1077546317714882
Xiang J, Liang M (2012) Wavelet-based detection of beam cracks using modal shape and frequency measurements. Comput Aided Civ Infrastruct Eng 27:439–454. https://doi.org/10.1111/j.1467-8667.2012.00760.x
Xin-She Y, Deb S (2009) Cuckoo Search via Levy flights. In: Nature & biologically inspired computing, 2009. NaBIC 2009. World Congress on, 9–11 December 2009, pp 210–214. https://doi.org/10.1109/nabic.2009.5393690
Xue X, Sun Q, Zhang L, Wu X (2011) Semi-active control strategy using genetic algorithm for seismically excited structure combined with MR damper. J Intell Mater Syst Struct 22:291–302. https://doi.org/10.1177/1045389x11399661
Yan G, Zhou LL (2006) Integrated fuzzy logic and genetic algorithms for multi-objective control of structures using MR dampers. J Sound Vib 296:368–382. https://doi.org/10.1016/j.jsv.2006.03.011
Yang G, Spencer BF, Carlson JD, Sain MK (2002) Large-scale MR fluid dampers: modeling and dynamic performance considerations. Eng Struct 24:309–323. https://doi.org/10.1016/S0141-0296(01)00097-9
Yang JN (1975) Application of optimal control theory to civil engineering structures. J Eng Mech Div 101(6):819–838
Zabihi-Samani M, Amini F (2015) A cuckoo search controller for seismic control of a benchmark tall building. J VibroEng 17:1382–1400
Zabihi-Samani M, Ghanooni-Bagha M (2017) A fuzzy logic controller for optimal structural control using MR dampers and particle swarm optimization. J VibroEng 19:1901–1914
Zabihi-Samani M, Ghanooni-Bagha M (2018) An optimal cuckoo search-Fuzzy logic controller for optimal structural control. Int J Optim Civil Eng 8:117–135
Zabihi-Samani M, Shayanfar M, Safiey A, Najari A (2018) Simulation of the behavior of corrosion damaged reinforced concrete beams with/without CFRP retrofit. Civ Eng J 4:958–970. https://doi.org/10.28991/cej-0309148
Zhou L, Chang C-C, Wang L-X (2003) Adaptive fuzzy control for nonlinear building-magnetorheological damper system. J Struct Eng 129:905–913. https://doi.org/10.1061/(asce)0733-9445(2003)129:7(905)
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Zabihi-Samani, M., Ghanooni-Bagha, M. Optimal Semi-active Structural Control with a Wavelet-Based Cuckoo-Search Fuzzy Logic Controller. Iran J Sci Technol Trans Civ Eng 43, 619–634 (2019). https://doi.org/10.1007/s40996-018-0206-0
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DOI: https://doi.org/10.1007/s40996-018-0206-0