Abstract
In this paper, a semi-actively tuned liquid column damper (TLCD) based on fuzzy neural networks (FNN) is proposed to vibration control of irregular buildings excited by multi-dimensional earthquake ground motions. The fuzzy neural networks method takes advantage of both neural networks and fuzzy controls and has the unique combination of ability to learn via nonlinear mapping of neural nets and the capacity to integrate expert knowledge via fuzzy rules. The fuzzy neural networks based on Takagi-Sugeno model is adopted in this research to actively adjust the orifice opening-area of the TLCD. An eccentric building equipped with two TLCDs arranged in perpendicular directions is used as an object for suppressing vibrations induced by multi-dimensional earthquake ground motions. For numerical simulations, a state space representation of the building-TLCD system is derived. Numerical simulations demonstrate that TLCDs regulated by the fuzzy neural networks are effective in controlling both the translational and rotational seismic response of the eccentric building.
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© 2005 Springer-Verlag Berlin Heidelberg
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Li, HN., Jin, Q., Song, G., Wang, GX. (2005). TLCD Semi-active Control Methodology of Fuzzy Neural Network for Eccentric Buildings. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3612. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539902_138
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DOI: https://doi.org/10.1007/11539902_138
Publisher Name: Springer, Berlin, Heidelberg
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