Amir Baghban - Professor, University of Gonabad

To control structures against wind and earthquake excitations, Adaptive Neuro Fuzzy Inference Systems and Neural Networks are combined in this study. The control scheme consists of an ANFIS inverse model of the structure to assess the control force. Unlike other methods, this approach doesn’t need other controllers to generate training data. Since the active ANFIS inverse controller may not guarantee a satisfactory response due to different uncertainties associated with operating conditions and noisy training data, this paper uses MR dampers as semi-active devices to provide control forces. To overcome the difficulty of tuning command voltage of MR dampers, a neural network inverse model is developed. The effectiveness of the proposed strategy is verified and illustrated using simulated response of the 3-story full-scale nonlinear benchmark building excited by several earthquake records through the computer simulation. Moreover, the recommended control algorithm is validated using the wind-excited 76-story benchmark building equipped with MR and TMD dampers. Comparing results with other controllers demonstrates that the proposed method can reduce displacement, drift and acceleration, significantly.

Control of structure, Semi-active control, ANFIS, MR damper