Adaptive Neuro-Fuzzy and Simple Adaptive Control Methods for Attenuating the Seismic Responses of Coupled Buildings with Semi-Active Devices: Comparative Study

Document Type : Regular Article


1 Texas A&M University

2 Texas A&M University, Zachry Department of Civil and Environmental Engineering

3 Texas A&M University, Zachry Department of Civil and Environmental Engineering, College Station, TX 77843


This paper describes two adaptive control methods for mitigating the seismic responses of two connected buildings with MR dampers at different levels. First method developed in this study is the adaptive neuro-fuzzy controller which consists of a fuzzy logic controller provided with learning algorithm based on adaptive neural networks. The learning algorithm is implemented to modify the parameters of the fuzzy logic controller such that its outputs track the behavior of predetermined training data. Second method is the simple adaptive controller which falls into the category of model-following adaptive strategies. In this method, a plant is commanded to follow a well-designed reference-model with desirable trajectories through a closed loop action. The coupled system consists of two adjacent buildings having different heights in order to separate the model shapes of the individual buildings. Different types of feedbacks such as displacement, velocity, and acceleration are employed to identify their impacts on the performance of the developed adaptive controllers. Numerical analyses are carried out for the complex system assuming no change in the nominal design parameters and then for the system where a change in these parameters is introduced. The results reveal that using the adaptive controllers developed in this study to regulate the MR dampers connecting the two adjacent buildings can successfully alleviate the seismic responses under various types and intensities of earthquakes.


Google Scholar


Main Subjects

[1] Barroso, L.R., S.E. Breneman, and H.A. Smith. Evaluating the effectiveness of structural control within the context of performance-based engineering. in Proceedings of the Sixth US National Conference on Earthquake Engineering, Seattle, Washington, Earthquake Engineering Research Institute. 1998.
[2] Westermo, B. D. (1989). The dynamics of interstructural connection to prevent pounding. Earthquake Engineering & Structural Dynamics, 18(5), 687–699. doi:10.1002/eqe.4290180508.
[3] Richardson, A., Walsh, K. K., & Abdullah, M. M. (2011). Closed-form equations for coupling linear structures using stiffness and damping elements. Structural Control and Health Monitoring, 20(3), 259–281. doi:10.1002/stc.490.
[4] Seto, K., Active vibration control of multiple buildings connected with active control bridges in response to large earthquakes. Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251), 1999. 2: p. 1007.
[5] Matsumoto, Y., Fukuda, Y., Doi, F., & Seto, K. (1998). Bending and Torsional Vibration Control for Flexible Structures arranged in Parallel. Transactions of the Japan Society of Mechanical Engineers Series C, 64(618), 414–420. doi:10.1299/kikaic.64.414.
[6] Mitsuta, S., Okawa, E., Seto, K., & Ito, H. (1994). Active Vibration Control of Structures Arranged in Parallel. JSME International Journal. Ser. C, Dynamics, Control, Robotics, Design and Manufacturing, 37(3), 436–443. doi:10.1299/jsmec1993.37.436.
[7] Yamada, Y., et al. Active control of structures using the joining member with negative stiffness. in Proc. First World Conference on Structural Control. 1994.
[8] Schurter, K. C., & Roschke, P. N. (2001). Neuro-fuzzy control of structures using acceleration feedback. Smart Materials and Structures, 10(4), 770–779. doi:10.1088/0964-1726/10/4/322.
[9] Dyke, S. J., Spencer, B. F., Sain, M. K., & Carlson, J. D. (1998). An experimental study of MR dampers for seismic protection. Smart Materials and Structures, 7(5), 693–703. doi:10.1088/0964-1726/7/5/012.
[10] Abdeddaim, M., Ounis, A., Shrimali, M. K., & Datta, T. K. (2017). Retrofitting of a weaker building by coupling it to an adjacent stronger building using MR dampers. Structural Engineering and Mechanics, 62(2), 197–208. doi:10.12989/sem.2017.62.2.197.
[11] Amini, F., & Doroudi, R. (2010). Control of a building complex with Magneto-Rheological Dampers and Tuned Mass Damper. Structural Engineering and Mechanics, 36(2), 181–195. doi:10.12989/sem.2010.36.2.181.
[12] Bharti, S. D., Dumne, S. M., & Shrimali, M. K. (2010). Seismic response analysis of adjacent buildings connected with MR dampers. Engineering Structures, 32(8), 2122–2133. doi:10.1016/j.engstruct.2010.03.015.
[13] Bhaskararao, A. and Jangid, R. (2004). Seismic response of adjacent buildings connected with dampers. in 13th World Conference on Earthquake Engineering.
[14] Uz, M. E., & Hadi, M. N. S. (2014). 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, 135–148. doi:10.1016/j.engstruct.2014.03.006.
[15] Gong, X., Ruan, X., Xuan, S., Yan, Q., & Deng, H. (2014). Magnetorheological Damper Working in Squeeze Mode. Advances in Mechanical Engineering, 6, 410158. doi:10.1155/2014/410158.
[16] Wong, C. W., Ni, Y. Q., & Lau, S. L. (1994). Steady‐State Oscillation of Hysteretic Differential Model. I: Response Analysis. Journal of Engineering Mechanics, 120(11), 2271–2298. doi:10.1061/(asce)0733-9399(1994)120:11(2271).
[17] Spencer, B. F., Dyke, S. J., Sain, M. K., & Carlson, J. D. (1997). Phenomenological Model for Magnetorheological Dampers. Journal of Engineering Mechanics, 123(3), 230–238. doi:10.1061/(asce)0733-9399(1997)123:3(230).
[18] Barkana, I. (2014). The beauty of simple adaptive control and new developments in nonlinear systems stability analysis. doi:10.1063/1.4904568.
[19] Kaufman, H., Bar-Kana, I., & Sobel, K. (1994). Direct Adaptive Control Algorithms: Theory and Applications. doi:10.1007/978-1-4684-0217-9.
[20] Symans, M. D., & Kelly, S. W. (1999). Fuzzy logic control of bridge structures using intelligent semi‐active seismic isolation systems. Earthquake Engineering & Structural Dynamics, 28(1), 37-60.
[21] Choi, K. M., Cho, S. W., Jung, H. J., & Lee, I. W. (2004). Semi‐active fuzzy control for seismic response reduction using magnetorheological dampers. Earthquake engineering & structural dynamics, 33(6), 723-736.
[22] Burns, R., Advanced control engineering. 2001: Elsevier.
[23] Al-Fahdawi, O. A. S., Barroso, L. R., & Soares, R. W. (2018). Utilizing the Adaptive Control in Mitigating the Seismic Response of Adjacent Buildings Connected with MR Dampers. 2018 Annual American Control Conference (ACC). doi:10.23919/acc.2018.8431135.
[24] Soares, R. W., Barroso, L. R., & Al-Fahdawi, O. A. S. (2018). Simple Adaptive Control Strategy Applied to Reduce Response of Bridge Structure Subjected to Changes in Plant. 2018 Annual American Control Conference (ACC). doi:10.23919/acc.2018.8431623.
[25] Ulrich, S., Hayhurst, D. L., Saenz Otero, A., Miller, D., & Barkana, I. (2014). Simple Adaptive Control for Spacecraft Proximity Operations. AIAA Guidance, Navigation, and Control Conference. doi:10.2514/6.2014-1288.
[26] Bitaraf, M., Hurlebaus, S., & Barroso, L. R. (2011). Active and Semi-active Adaptive Control for Undamaged and Damaged Building Structures Under Seismic Load. Computer-Aided Civil and Infrastructure Engineering, 27(1), 48–64. doi:10.1111/j.1467-8667.2011.00719.
[27] Amini, F., Bitaraf, M., Eskandari Nasab, M. S., & Javidan, M. M. (2018). Impacts of soil-structure interaction on the structural control of nonlinear systems using adaptive control approach. Engineering Structures, 157, 1–13. doi:10.1016/j.engstruct.2017.11.071.
[28] Jang, J.-S. (1993). ANFIS: adaptive-network-based fuzzy inference system. IEEE transactions on systems, man, and cybernetics, 23(3): p. 665-685.
[29] Jang, J. S. R., Sun, C. T., & Mizutani, E. (1997). Neuro-Fuzzy and Soft Computing-A Computational Approach to Learning and Machine Intelligence [Book Review]. IEEE Transactions on Automatic Control, 42(10), 1482–1484. doi:10.1109/tac.1997.633847.
 [30] Schurter, K. C., & Roschke, P. N. (2001). Neuro-fuzzy control of structures using magnetorheological dampers. Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148). doi:10.1109/acc.2001.945866.
[31] Barkana, I., & Guez, A. (1990). Simple adaptive control for a class of non-linear systems with application to robotics. International Journal of Control, 52(1), 77–99. doi:10.1080/00207179008953525
[32] Ioannou, P. and P. Kokotovic, Adaptive Systems with Reduced Models. Springer-Verlag, Berlin, 1983.
[33] Ramallo, J., Johnson, E., & Spencer, B. F. (2002). “Smart” base isolation systems. Journal of Engineering Mechanics, 128(10): p. 1088-1099.
[34] Al-Fahdawi, O. A. S., Barroso, L. R., & Soares, R. W., Simple adaptive control method for mitigating the seismic responses of coupled adjacent buildings considering parameter variations. Engineering Structures, 2019, 186, 369–381. doi:10.1016/j.engstruct.2019.02.025.
[35] Spencer B. F. Reliability of randomly excited hysteretic structures. Lecture Notes in Eng 1986.
[36] Tse T., & Chang C. C. Shear-mode rotary magnetorheological damper for small-scale structural control experiments. J Struct Eng 2004; 130(6): 904–11. 10.1061/(asce)0733-9445(2004)130:6(904).
[37] Al-Fahdawi, O. A. S., Barroso, L. R., & Soares, R. W. (2019). Simple adaptive control for enhancing the seismic performance of nonlinear coupled buildings with smooth hysteretic behavior. Engineering Structures, 191, 536–548. doi:10.1016/j.engstruct.2019.02.025.