چکیده مقاله
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
کلیدواژهها
نویسندگان
Abbas Karamodin
Assistant professor, Department of Civil Engineering, Ferdowsi University of Mashhad
Amir Baghban
PhD Student, Department of Civil Engineering, Ferdowsi University of Mashhad
شیوه ارجاع
Karamodin, Abbas and Baghban, Amir,1391,Neuro-predictive Algorithm for Structural Control,9th International Congress on Civil Engineering,Isfahan
ارائهشده در
مجموعه مقالات نهمین کنگره بین الملی مهندسی عمران19 اردیبهشت 1391 · اصفهان