Numerical simulation of active structural control based on dynamic fuzzy neural network

In the area of fuzzy control for civil structures, how to generate fuzzy rules for structural vibration control is a key issue. In this paper, a dynamic fuzzy neural network (DFNN) algorithm is adopted to extract fuzzy rules based on the sample data obtained from the performance of the system under optimal control algorithm. First, the structure and algorithm of DFNN is introduced. Then, a fuzzy controller is designed using DFNN algorithm for a five-story frame controlled by an active mass damper. The simulation results show that the fuzzy controller is very effective in reducing the response of model structure under seismic excitation. Moreover, the robustness of the fuzzy controller is validated through the change of seismic input and structural parameters. The proposed method is referential to the design of fuzzy controller and can provide a necessary foundation for the practical structural control.