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논문 기본 정보

자료유형
학술저널
저자정보
Baghban, Amir (Department of Civil Engineering, Ferdowsi University of Mashhad) Karamodin, Abbas (Department of Civil Engineering, Ferdowsi University of Mashhad) Haji-Kazemi, Hasan (Department of Civil Engineering, Ferdowsi University of Mashhad)
저널정보
테크노프레스 Smart structures and systems Smart structures and systems 제16권 제6호
발행연도
2015.1
수록면
1,133 - 1,145 (13page)

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A new neural network (NN) predictive controller (NNPC) algorithm has been developed and tested in the computer simulation of active control of a nonlinear structure. In the present method an NN is used as a predictor. This NN has been trained to predict the future response of the structure to determine the control forces. These control forces are calculated by minimizing the difference between the predicted and desired responses via a numerical minimization algorithm. Since the NNPC is very time consuming and not suitable for real-time control, it is then used to train an NN controller. To consider the effectiveness of the controller on probability of damage, fragility curves are generated. The approach is validated by using simulated response of a 3 story nonlinear benchmark building excited by several historical earthquake records. The simulation results are then compared with a linear quadratic Gaussian (LQG) active controller. The results indicate that the proposed algorithm is completely effective in relative displacement reduction.

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