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Decentralized output feedback polynomial control of seismically excited structures using genetic algorithm
Author(s) -
Cha YoungJin,
Agrawal Anil K.
Publication year - 2013
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.486
Subject(s) - benchmark (surveying) , control theory (sociology) , polynomial , displacement (psychology) , genetic algorithm , representation (politics) , controller (irrigation) , sample (material) , control (management) , computer science , optimal control , mathematics , mathematical optimization , artificial intelligence , physics , mathematical analysis , law , psychology , agronomy , geodesy , politics , political science , psychotherapist , biology , geography , thermodynamics
SUMMARY This paper presents novel decentralized output feedback control strategy for the active and semi‐active controls of the highway bridge benchmark phases I and II problems subjected to earthquake ground motions. The control force is calculated using two third‐order polynomial equations expressing a direct relationship between displacement and velocity of the control device and the control force. An advanced implicit redundant representation genetic algorithm is utilized to determine optimal coefficients of the two polynomial equations by minimizing the sum of three evaluation criteria for six prescribed earthquakes. The performance of the proposed controller is evaluated in terms of a set of prescribed 21 evaluation criteria and is compared with the other several control strategies published in the special issue of the benchmark problem. The results show that the proposed decentralized output feedback polynomial control strategy can achieve significant response reductions in the bridge system, and it is evidently superior to sample control strategies and other suggested active and semi‐active controls for the phase I problem and is quite competitive with respect to the sample and other semi‐active control approaches for the fully isolated phase II problem. Copyright © 2011 John Wiley & Sons, Ltd.