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Control issues relating to real‐time substructuring experiments using a shaking table
Author(s) -
Neild S. A.,
Stoten D. P.,
Drury D.,
Wagg D. J.
Publication year - 2005
Publication title -
earthquake engineering and structural dynamics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.218
H-Index - 127
eISSN - 1096-9845
pISSN - 0098-8847
DOI - 10.1002/eqe.473
Subject(s) - substructure , earthquake shaking table , structural engineering , control theory (sociology) , engineering , remainder , actuator , damper , process (computing) , transfer function , controller (irrigation) , computer science , control (management) , mathematics , agronomy , arithmetic , electrical engineering , artificial intelligence , biology , operating system
Real‐time substructuring is a method of dynamically testing a structure without experimentally testing a physical model of the entire system. Instead the structure can be split into two linked parts, the region of particular interest, which is tested experimentally, and the remainder which is tested numerically. A transfer system, such as a hydraulic actuator or a shaking table, is used to impose the displacements at the interface between the two parts on the experimental substructure. The corresponding force imposed by the substructure on the transfer system is fed back to the numerical model. Control of the transfer system is critical to the accuracy of the substructuring process. A study of two controllers used in conjunction with the University of Bristol shaking table is presented here. A proof‐of‐concept one degree‐of‐freedom mass–spring–damper system is substructured such that a portion of the mass forms the experimental substructure and the remainder of the mass plus the spring and the damper is modelled numerically. Firstly a linear controller is designed and tested. Following this an adaptive substructuring strategy is considered, based on the minimal control synthesis algorithm. The deleterious effect of oil‐column resonance common to shaking tables is examined and reduced through the use of filters. The controlled response of the experimental specimen is compared for the two control strategies. Copyright © 2005 John Wiley & Sons, Ltd.