COMPENSATION FOR THE DELAY OF THE REAL-TIME SUBSTRUCTURE EXPERIMENT BY USING NEURAL NETWORK PREDICTION

The major problem of real-time substructure experiment lies in the delay of the hydraulic press servo actuator, causing a direct influence on the stability and veracity. It is proposed to adopt neuro-network prediction to compensate for the delay. The experimental setup is established consisting of D-space real-time simulator, hydraulic actuator, measuring system, data collecting system and measure the value of the delayed time of actuator. On the basis of that, the trained neuro-network is used to compensate for the delay, so that the numerical model and the experimental Substructure can be coordinated and transfigured. Finally, a real-time substructure experiment is performed on a three-storied structure under seismic excitation, which proves the validity of this method.