Modal-Energy-Based Neuro-Controller for Seismic Response Reduction of a Nonlinear Building Structure

Abstract

This study presents a neuro-control algorithm based on structural modal energy that outputs an optimal control signal to reduce vibration during earthquakes. The modal energy of a structure is used in the objective function during the training process of a neural network. The modal energy and control signal are then minimized by the proposed neuro-control technique. A three-story nonlinear building was installed with an active mass damper, which was used to verify the applicability of the proposed control algorithm. The El Centro earthquake was adopted to train the modal-energy-based neuro-controller. The six recorded earthquakes were employed to consider unknown earthquake effects after training. The results obtained from the proposed control algorithm were compared with those obtained from a non-controlled response and a multilayer perceptron. The numerical results show that the proposed control algorithm is quite effective in reducing the structural response and modal energy. While nonlinear hysteretic behaviors appear in the non-controlled responses, these nonlinear behaviors almost entirely disappear with control.