Adaptive Kriging multi-objective reliability-based design optimization of fuzzy logic controller for mr damper structures

Dynamic loads from natural hazards, such as severe earthquakes and strong winds, can induce excessive vibrations, displacements, and stresses in structures, potentially compromising their stability, functionality, and safety [1-2].To mitigate these effects, magnetorheological (MR) dampers have emerged as effective semi-active control devices due to their ability to provide adjustable damping forces with rapid response times [3].However, the presence of inherent uncertainties, including variations in structural properties, environmental conditions, and external loadings, poses significant challenges to the performance of MR dampers [4][5].Addressing these uncertainties is crucial for ensuring the reliability and robustness of MR dampers in real-world applications [6].Therefore, the development of advanced control strategies and optimization techniques is essential to enhance their adaptive capabilities, minimize failure risks, and improve overall structural safety in the face of unpredictable dynamic events.To develop an optimal and reliable control system for MR damper-based structural systems, a fuzzy logic controller (FLC) is employed, and a reliability-based design optimization (RBDO) framework is formulated to determine the optimal FLC parameters.This framework aims to minimize two key objectives related to the inter-story drift and average control force while satisfying probabilistic constraints to account for uncertainties in dynamical system.Two RBDO methods are proposed to solve the RBDO problem.The first method combines a deterministic design optimization-based global Kriging model with the non-dominated sorting genetic algorithm (NSGA-II) to solve the multi-objective optimization problem, referred to as DDO-GK-MO.While this approach is effective, it operates within a deterministic framework