Neuro-predictive Algorithm for Structural Control

سال انتشار: 1391
محل انتشار: نهمین کنگره بین الملی مهندسی عمران
کد COI اختصاصی: ICCE09_833
زبان مقاله: انگلیسی
تعداد مشاهده: 1269

نویسندگان

Assistant professor, Department of Civil Engineering, Ferdowsi University of Mashhad

PhD Student, Department of Civil Engineering, Ferdowsi University of Mashhad

چکیده

A new neural network (NN) predictive controller (NNPC) algorithm has been developed and tested in the computer simulation of active control of nonlinear benchmark buildings. Although in classical model predictive control (MPC) usually a linear model of structure is used, NNPC provides a nonlinear model. In the present method an NN is used as an emulator. This emulator NN has been trained to predict the future response of the structure. The trained NN provides a model of structure which is employed todetermine the control force via a numerical minimization algorithm. Since the NNPC controller is very time consuming and not suitable for real-time control, it is then used to train a NN controller. The approach is validated by using simulated response of a 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 effective in relative displacement reduction which is here selected for control.

کلیدواژه ها

Structural control, Active controller, Neural network controller, Neuro-predictive algorithm, Model predictive control (MPC

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