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Supervisory fuzzy control of a base‐isolated benchmark building utilizing a neuro‐fuzzy model of controllable fluid viscous dampers
Author(s) -
Reigles Damon G.,
Symans Michael D.
Publication year - 2006
Publication title -
structural control and health monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 62
eISSN - 1545-2263
pISSN - 1545-2255
DOI - 10.1002/stc.108
Subject(s) - damper , base isolation , benchmark (surveying) , structural engineering , control theory (sociology) , engineering , magnetorheological fluid , controller (irrigation) , reduction (mathematics) , fuzzy logic , controllability , computer science , mathematics , geology , control (management) , mechanical engineering , geodesy , frame (networking) , artificial intelligence , agronomy , geometry , biology
Abstract A numerical study demonstrating the effectiveness of a supervisory fuzzy controller for seismic protection of a base‐isolated structure is described in this paper. The numerical simulations were conducted using the first‐generation base isolation benchmark problem. This benchmark problem focuses on the three‐dimensional seismic response of an eight‐storey base‐isolated building wherein lateral–torsional response of the plan irregular structure is explicitly modeled. The isolation system consists of low‐damping elastomeric bearings and semi‐active controllable fluid viscous dampers. The dynamics of the controllable fluid viscous dampers are accounted for via a neuro‐fuzzy model that is developed based on experimental data from testing of small‐scale controllable fluid viscous dampers. Results from the simulations demonstrate that accounting for the damper dynamics is important in assessing the realizable improvements in seismic response reduction. Furthermore, the results show that simultaneous reductions in peak isolation system deformation and peak superstructure responses can be achieved for several near‐field earthquake ground motions, particularly with respect to the semi‐active clipped optimal sample controller provided in the benchmark problem statement Copyright © 2005 John Wiley & Sons, Ltd.