Neuro-genetic algorithm for non-linear active control of structures

In a companion paper, a new non-linear control model was presented I-or active control of three-dimensional (3D) building structures including geometrical and material non-linearities, coupling action between lateral and torsional motions, and actuator dynamics (Int. J. Numer Meth. Engng; DOI: 10.1002/nme.2195). A dynamic fuzzy wavelet neuroemulator was presented for predicting the structural response in future time steps. In this paper, a new neuro-genetic algorithm or controller is presented for finding the optimal control forces. The control algorithm does not need the pre-training required in a neural network-based controller, which improves the efficiency of the general control methodology significantly. Two 3D steel building structures, a 12-story structure with vertical setbacks and an 8-story structure with plan irregularity, are used to validate the neuro-genetic control algorithm under three different seismic excitations. Numerical validations demonstrate that the new control methodology significantly reduces the displacements of buildings Subjected to various seismic excitations including structures with plan and elevation irregularities. Copyright (c) 2008 John Wiley & Sons, Ltd.