Hybrid Optimization Algorithm Based on Whale Optimization and Fuzzy Logic for Magnetorheological Dampers
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Introduction: to mitigate vibrations in structures subjected to dynamic loads, magnetorheological (MR) dampers have been studied as an effective solution to reduce the forces and deformations caused by these loads. Due to their highly nonlinear behavior, it is necessary to implement nonlinear control algorithms to achieve optimal control forces that minimize the response of the structures.
Objective: this study aims to reduce the response of a real building located in Medellín, Colombia, equipped with MR dampers. The goal is to optimize a fuzzy logic controller, using Gaussian membership functions that will be enhanced through the whale optimization algorithm, to find the appropriate voltage to be applied to the damper and generate optimal damping forces.
Results: the results show that the implementation of a set of MR dampers, controlled by fuzzy logic and optimized with the whale algorithm, significantly reduces the structural response to seismic loads. Reductions of 68% in displacement, 42% in velocity, 12% in acceleration, 42% in interstory drift, and 75% in the RMS value of displacement were observed compared to a system without control.
Conclusions: the application of the proposed controller proves to be effective in enhancing the performance of magnetorheological dampers in reducing the structural response to dynamic loads, highlighting its potential in the design of control systems for vibration mitigation in buildings.
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Accepted 2024-09-12
Published 2024-09-23
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