Cooperative Coevolution Fuzzy Control of MR Damper for Damage Reduction of Structures

Document Type : Research Article

Authors

1 Department of Civil Engineering, Ferdowsi University, Mashhad, Iran

2 Center of Excellence for Engineering and Management of Civil Infrastructures, School of Civil Engineering, Faculty of Engineering. The University of Tehran, Tehran, Iran

3 Department of Civil Engineering, Arak Branch, Islamic Azad University, Arak, Iran

Abstract

In this research, damage reduction of structures is studied using semi-active control of MR dampers. Fuzzy control is an intelligent control method in contrast to classical control with some specific capabilities such as handling non-linear and complex systems, adaptability and robustness to errors and uncertainties. However, due to lack of learning ability of fuzzy controller, it is used in combination with a genetic algorithm, which in turn suffers from some problems like premature convergence around an incorrect target.Therefore, in this research, the introduction of the cooperative coevolution fuzzy controller in which the parameters of membership functions and rules will be searched in two separate species. To investigate and compare the performance of this controller with some other controllers, these methods are implemented on a three story benchmark nonlinear structure. The results showed that the performance of the cooperative coevolution fuzzy controller is better than the other controllers and can reduce the average damage of the structure up to %79.

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[1] G.W. Housner, L.A. Bergman, T.K. Caughey, A.G. Chassiakos, R.O. Claus, S.F. Masri, R.E. Skelton, T. Soong, B. Spencer, J.T. Yao, Structural control: past, present, and future, Journal of engineering mechanics, 123(9) (1997) 897-971.
[2] C.H. Loh, L. Wu, P. Lin, Displacement control of isolated structures with semiactive control devices, Structural Control and Health Monitoring, 10(2) (2003) 77-100.
[3] B. Samali, M. Al-Dawod, Performance of a five-storey benchmark model using an active tuned mass damper and a fuzzy controller, Engineering Structures, 25(13) (2003) 1597-1610.
[4] M. Al-Dawod, B. Samali, K. Kwok, F. Naghdy, Fuzzy controller for seismically excited nonlinear buildings, Journal of Engineering Mechanics, 130(4) (2004) 407-415.
[5] B. Samali, M. Al-Dawod, K.C. Kwok, F. Naghdy, Active control of cross wind response of 76-story tall building using a fuzzy controller, Journal of engineering mechanics, 130(4) (2004) 492-498.
[6] D.G. Reigles, M.D. Symans, Supervisory fuzzy control of a base-isolated benchmark building utilizing a neuro-fuzzy model of controllable fluid viscous dampers, Structural Control and Health Monitoring, 13(2-3) (2006) 724-747.
[7] S. Pourzeynali, H. Lavasani, A. Modarayi, Active control of high rise building structures using fuzzy logic and genetic algorithms, Engineering Structures, 29(3) (2007) 346-357.
[8] A. Khajekaramodin, Earthquake damage control of structures using genetic fuzzy algorithms, Ferdowsi University, 2010 (In persian:کرم الدین، عباس، " کنترل خسارت سازه ها در برابر زلزله به روش ژنتیک فازی"، رساله دکتری، دانشگاه فردوسی مشهد 1388)).
[9] Karamodin, Irani, Baghban, The effect of fuzzy controller on reducing the damage to structures, in: Sixth National Congress on Civil Engineering, 2011 (In persian: کرم الدین، عباس، ایرانی، فریدون، باغبان خیابانی، امیر، " اثر کنترل کننده فازی بر کاهش میزان خسارت سازه ها"، ششمین کنگره ملی مهندسی عمران، 1390
[10] M.E. Uz, M.N. Hadi, Optimal design of semi active control for adjacent buildings connected by MR damper based on integrated fuzzy logic and multi-objective genetic algorithm, Engineering Structures, 69 (2014) 135-148.
[11] T.J. Ross, Fuzzy Logic with Engineering Applications, (2004).
[12] C. Oscar, H. Francisco, H. Frank, Genetic Fuzzy Systems: Evolutionary tuning and learning of fuzzy knowledge bases, World Scientific, 2001.
[13] Z.-S. Huang, C. Wu, D.-S. Hsu, Semi-active fuzzy control of mr damper on structures by genetic algorithm, Journal of Mechanics, 25(1) (2009) N1-N6.
[14] M.R. Elhami, C. Daneshdoost, D. Madady, Semi-active Control of Structure Vibrations with MR Damper Using Fuzzy Control System (FLC) and Optimization through Genetic Algorithm (GA), in: Advances in computer, communication, control and automation, Springer, 2011, pp. 583-590.
[15] C.A. Pena-Reyes, M. Sipper, Fuzzy CoCo: A cooperative-coevolutionary approach to fuzzy modeling, IEEE Transactions on fuzzy systems, 9(5) (2001) 727-737.
[16] M.A. Potter, The design and analysis of a computational model of cooperative coevolution, Citeseer, 1997.
[17] M.A. Potter, K.A.D. Jong, Cooperative coevolution: An architecture for evolving coadapted subcomponents, Evolutionary computation, 8(1) (2000) 1-29.
[18] M.S. Williams, R.G. Sexsmith, Seismic damage indices for concrete structures: a state-of-the-art review, Earthquake spectra, 11(2) (1995) 319-349.
[19] Y. Ohtori, R. Christenson, B. Spencer Jr, S. Dyke, Benchmark control problems for seismically excited nonlinear buildings, Journal of Engineering Mechanics, 130(4) (2004) 366-385.
[20] S. Dyke, B. Spencer Jr, M. Sain, J. Carlson, Modeling and control of magnetorheological dampers for seismic response reduction, Smart materials and structures, 5(5) (1996) 565.
[21] G. Yang, B. Spencer Jr, J. Carlson, M. Sain, Large-scale MR fluid dampers: modeling and dynamic performance considerations, Engineering structures, 24(3) (2002) 309-323.