The article presents a model-based fuzzy controller design method for seismic response reduction of building structures using MR dampers. Firstly, the MR damper model is obtained as a fuzzy model using T-S fuzzy modeling technique; then, this model is integrated with the linear structural model to formulate a fuzzy system; at last, the optimal control strategy, such as GH2 (generalized H2 or energy-to-peak) control of which objective is to minimize the peak value of control output under energy-bounded disturbance, is applied to design the fuzzy controller. The advantage of this new control strategy is that the optimal control theory can be directly applied to design a fuzzy controller such that the closed-loop system stability and performance can be theoretically guaranteed. In addition, the command signal can be obtained directly from the measured feedback signals. A numerical example is used to validate the effectiveness of the proposed approach. It is confirmed by the simulations that the designed controller achieves better performance than existing semi-active control strategies such as clipped-optimal control and fuzzy control.
Angelov, P.P. and Filev, D.P.2004. ``An Approach to Online Identification of Takagi-Sugeno Fuzzy Models,'' IEEE Transactions on Systems, Man and Cybernetics-Part B: Cybernetics, 34(1):484-498.
2.
Chang, C.C. and Roschke, P.N.1998. ``Neural Network Modeling of a Magnetorheological Damper ,'' Journal of Intelligent Material Systems and Structures , 9(9):755-764.
3.
Chang, C.C. and Zhou, L.2002. ``Neural Network Emulation of Inverse Dynamics for a Magnetorheological Damper,'' Journal of Structural Engineering, 128(2):231-239.
4.
Choi, K.M., Cho, S.W., Jung, H.J. and Lee, I.W.2004. ``Semi-active Fuzzy Control for Seismic Response Reduction using Magnetorheological Dampers,'' Earthquake Engineering and Structural Dynamics, 33:723-736.
5.
Du, H. and Zhang, N.2007. ``Linear Modeling of Magnetorheological Dampers using Hybrid Intelligence Technique,'' In: Proceedings of the 14th International Congress on Sound and Vibration, Cairns, Australia, pp. 9-12.
6.
Du, H. and Zhang, N.2008. ``Application of Evolving Takagi-Sugeno Fuzzy Model to Non-linear System Identification,'' Applied Soft Computing , 8:676-686.
7.
Dyke, S.J. and Spencer, B.F.1997. ``A Comparison of Semi-active Control Strategies for the MR Damper,'' In: IASTED International Conference on Intelligent Information Systems, Grand Bahama Island, Bahamas, pp. 580-584.
8.
Dyke, S.J., Spencer, B.F., Sain, M.K. and Carlson, J.D.1996. ``Modeling and Control of Magnetorheological Dampers for Seismic Response Reduction,'' Smart Materials and Structures , 5(5):565-575.
9.
Dyke, S.J., Spencer, B.F., Sain, M.K. and Carlson, J.D.1998. ``An Experimental Study of MR Dampers for Seismic Protection ,'' Smart Materials and Structures, 7:693-703.
10.
Fang, C.-H., Liu, Y.-S., Kau, S.-W., Hong, L. and Lee, C.-H.2006. ``A New LMI-based Approach to Relaxed Quadratic Stabilization of T-S Fuzzy Control System,'' IEEE Transactions on Fuzzy Systems, 14(3):386-397.
11.
Feng, G.2006. ``A Survey on Analysis and Design of Model-based Fuzzy Control Systems,'' IEEE Transactions on Fuzzy Systems, 14(5):676-697.
12.
Huang, H., Pasquier, M. and Quek, C.2006. ``Optimally Evolving Irregular-shaped Membership Functions for Fuzzy Systems,'' In: Proceedings of 2006 IEEE Congress on Evolutionary Computation, Vancouver, BC, Canada, pp. 3309-3316.
13.
Jansen, L.M. and Dyke, S.J.2000. ``Semiactive Control Strategies for MR Dampers: Comparative Study,'' Journal of Engineering Mechanics, 126(8):795-803.
14.
Kim, M.S., Kim, C.H. and Lee, J.J.2006. ``Evolving Compact and Interpretable Takagi-Sugeno Fuzzy Models with a New Encoding Scheme,'' IEEE Transactions on Systems, Man and Cybernetics-Part B: Cybernetics, 36(5):1006-1023.
15.
Lotfi, A. and Tsoi, A.C.1994. ``Importance of Membership Functions: a Comparative Study on Different Learning Methods for Fuzzy Inference Systems,'' In: Proceedings of the ThirdIEEE World Congress on Fuzzy Systems, Orlando, FL, USA, pp. 1791-1796.
16.
Sala, A., Guerra, T.M. and Babuska, R.2005. ``Perspectives of Fuzzy Systems and Control, '' Fuzzy Sets and Systems, 156: 432-444.
17.
Spencer, B.F., Dyke, S.J., Sain, M.K. and Carlson, J.D.1997. ``Phenomenological Model for Magnetorheological Dampers ,'' Journal of Engineering Mechanics, 123(3):230-238.
18.
Tamaki, F.Kanagawa, A. and Ohta, H.1998. ``Identification of Membership Functions Based on Fuzzy Observation Data,'' Fuzzy Sets and Systems, 93:311-318.
19.
Ting, C.-S.2006. ``Stability Analysis and Design of Takagi-Sugeno Fuzzy Systems,'' Information Sciences, 176:2817-2845.
20.
Wang, D.H. and Liao, W.H.2005. ``Modeling and Control of Magnetorheological Fluid Dampers Using Neural Networks,'' Smart Materials and Structures, 14:111-126.
21.
Xu, Z.-D., Shen, Y.-P. and Guo, Y.-Q.2003. ``Semi-active Control of Structures Incorporated with Magnetorheological Dampers using Neural Networks,'' Smart Materials and Structures, 12:80-87.
22.
Xu, Z.-D. and Guo, Y.-Q.2006. ``Fuzzy Control Method for Earthquake Mitigation Structures with Magnetorheological Dampers,'' Journal of Intelligent Material Systems and Structures, 17:871-881.
23.
Xu, Z.-D. and Shen, Y.-P.2003. ``Intelligent Bi-state Control for the Structure with Magnetorheological Dampers,'' Journal of Intelligent Material Systems and Structures, 14:35-42.
24.
Yan, G. and Zhou, L.L.2006. ``Integrated Fuzzy Logic and Genetic Algoritms for Multi-objective Control of Structures using MR Dampers,'' Journal of Sound and Vibration, 296:368-382.
25.
Yang, J.N., Lin, S. and Jabbari. F.2001. ``Performance-based Controller for Civil Engineering Structures,'' In: Proceedings of the American Control Conference , Arlington, VA, USA, pp. 1083-1088.
26.
Yang, J.N., Lin, S. and Jabbari, F.2003. ``H2-based Control Strategies for Civil Engineering Structures ,'' Journal of Structural Control, 10:205-230.
27.
Yi, F., Dyke, S.J., Caicedo, J.M. and Carlson, J.D.2001. ``Experimental Verification of Multiinput Seismic Control Strategies for Smart Dampers,'' Journal of Engineering Mechanics , 127(11):1152-1164.
28.
Zeng, X.-J. and Singh, M.G.1996. ``A Relationship Between Membership Functions and Approximation Accuracy in Fuzzy Systems,'' IEEE Transactions on Systems, Man and Cybernetics-Part B: Cybernetics, 26(1):176-180.
