Study of Seismic Response and Optimization of Control Forces For Magnetorheological Damper in 3D-Frame using AMGA-VEGA-MOGA with Fuzzy Controller

Abstract

This study investigates the reduction of seismic effects in three-dimensional framed  structures using magnetorheological (MR) dampers integrated with intelligent control strategies.  The research focuses on determining optimal control forces to minimize lateral displacement and  inter-story drift under earthquake loading. Three genetic algorithms Adaptive and Modular  Genetic Algorithm (AMGA), Vector Evaluation Genetic Algorithm (VEGA), and Multi-Objective  Genetic Algorithm (MOGA) are individually combined with a fuzzy logic controller. Displacement and velocity are used as input parameters, while the control output regulates the  voltage applied to the MR dampers, thereby adjusting their damping force in real time. A realistic  3D frame model representing part of an actual building, equipped with eight MR dampers and  subjected to recorded ground acceleration histories, was developed and analyzed in MATLAB. Comparative evaluation of the hybrid controllers yielded reductions in both maximum floor drift (25.74%) and maximum RMS displacement (32.2%). The performance advantage in the Y direction yielded the highest reductions for both floor drift (16.92%) and RMS displacement (33.45%). Overall, the primary objective is to recenter the building and reduce structural  movements with the aid of these algorithms.