Abstract
With the trend toward taller and more flexible building structures, the use of vibration control devices, passive as well as active, as means of structural protection against strong wind and earthquakes have received significant attention in recent years. A mass-damper shaking table system has been considered as means for vibration suppression to external excitation and disturbances. No explicitly system identification of the plant dynamics, no membership function and thus no fuzzification–defuzzification operation are required. For effective control performance, a neural classifier controller with genetic algorithm is developed. Compared with the conventional neural network and fuzzy controller, the neural classifier controller using genetic algorithm has been presented with the effectiveness of the vibration suppression control. Experimental results show that the neural classifier controller remains effective for building structure vibration suppression under free vibration and forced vibration excitation.
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Yang SM, Lee GS (1997) Vibration control of smart structures by using neural networks. J Dyn Syst Meas Control ASME 119(1):34–39
Yang SM, Lee GS (1997) A neural network design methodology for structural control. In: 1997 ASME Design Engineering Technical Conferences, paper no. DETC97/VIB-3775
Yang SM, Lee GS (1997) System identification of smart structures using neural networks. J Intellect Mater Syst Struct 8(10):883–890
Yang SM, Chen CJ, Huang WL (2006) Structural vibration suppression by a neural-network controller with a mass-damper actuator. J Vib Control 12(5):495–508
Chen CJ, Yang SM, Wang ZC (2009) System identification by neuro-fuzzy model with Sugeno and Mamdani fuzzy rules. J Aeronaut Astronaut Aviat 41(4):263–270
Yan SZ, Zheng K, Li Y (2005) Vibration suppression of adaptive truss structure using fuzzy-neural network. In: Wang J, Liao X, Yi Z (eds) Advances in neural networks-ISNN05. Springer, LNCS 3498, Part III, pp 155–160
Cavallo A, De Maria G, Natale C (2001) Second order sliding manifold approach for vibration reduction via output feedback: experimental results. IEEE/ASME Int Conf Adv Intell Mechatron Proc 2:725–730
Li Y, Liu Y, Liu X (2005) Active vibration control of a modular robot combining a BP neural network with a genetic algorithm. J Vib Control 11(1):3–17
Li Y, Liu Y, Liu X, Peng ZY (2004) Parameter identification and vibration control in modular manipulators. IEEE/ASME Trans Mechatron 9(4):700–705
Kundu S, Seto K, Sugino S (2002) Genetic algorithm application to vibration control of tall flexible structures. IEEE Proc Electron Design Test Appl 333–337
Minato J, Ohsumi A (2003) Control for high-rise buildings subjected to wind and seismic disturbances. In: SICE 2003 annual conference, vol 1, pp 535–539
Itoh K, Iwasaki M, Matsui N (2004) Optimal design of robust vibration suppression controller using genetic algorithms. IEEE Trans Ind Electron 51(5):947–953
Kohonen T (1988) Self-organization and associative memory. Springer, Berlin
Holland JH (1975) Adaptation in natural and artificial systems. The University of Michigan Press, Ann Arbor
Rechenberg I (1973) Evolutionsstrategie—Optimierung Technischer Systeme Nach Prinzipien der Biologischen Evolution. Frommann-Holzboog, Stuttgart
Schwefel HP (1981) Genetic algorithms and simulated annealing. Wiley, Chichester
Fogel LJ, Owens AJ, Walsh MJ (1966) Artificial intelligence through simulated evolution. Wiley, New York
Fogel DB (1994) An introduction to simulated evolutionary optimization. IEEE Trans Neural Netw 5(1):3–14
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Chen, CJ. Structural vibration suppression by using neural classifier with genetic algorithm. Int. J. Mach. Learn. & Cyber. 3, 215–221 (2012). https://doi.org/10.1007/s13042-011-0053-9
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DOI: https://doi.org/10.1007/s13042-011-0053-9