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Seismic control response of structures using an ATMD with fuzzy logic controller and PSO method
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  • Seismic control response of structures using an ATMD with fuzzy logic controller and PSO method
  • Seismic control response of structures using an ATMD with fuzzy logic controller and PSO method
저자명
Shariatmadar. Hashem,Razavi. Hessamoddin Meshkat
간행물명
Structural engineering and mechanics : An international journal
권/호정보
2014년|51권 4호|pp.547-564 (18 pages)
발행정보
테크노프레스
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

This study focuses on the application of an active tuned mass damper (ATMD) for controlling the seismic response of an 11-story building. The control action is achieved by combination of a fuzzy logic controller (FLC) and Particle Swarm Optimization (PSO) method. FLC is used to handle the uncertain and nonlinear phenomena while PSO is used for optimization of FLC parameters. The FLC system optimized by PSO is called PSFLC. The optimization process of the FLC system has been performed for an 11-story building under the earthquake excitations recommended by International Association of Structural Control (IASC) committee. Minimization of the top floor displacement has been used as the optimization criteria. The results obtained by the PSFLC method are compared with those obtained from ATMD with GFLC system which is proposed by Pourzeynali et al. and non-optimum FLC system. Based on the parameters obtained from PSFLC system, a global controller as PSFLCG is introduced. Performance of the designed PSFLCG has been checked for different disturbances of far-field and near-field ground motions. It is found that the ATMD system, driven by FLC with the help of PSO significantly reduces the peak displacement of the example building. The results show that the PSFLCG decreases the peak displacement of the top floor by about 10%-30% more than that of the FLC system. To show the efficiency and superiority of the adopted optimization method (PSO), a comparison is also made between PSO and GA algorithms in terms of success rate and computational processing time. GA is used by Pourzeynali et al for optimization of the similar system.