A hybrid metaheuristic method for optimization of active tuned mass dampers

Abstract

A metaheuristic‐based tuning methodology for the optimization of active tuned mass dampers (ATMDs) is presented. The methodology considers both physical parameters of ATMDs and controller parameters of the control algorithm. The employed control algorithm is a proportional–integral–derivative type controller. ATMDs are used in structures in the reduction of structural responses resulted from earthquakes. The proposed methodologies must be feasible for real practices in construction, so consider all physical factors such as stroke capacity, limitation of the active control force, the time delay of the generated control signal, and a time‐saving one. A novel hybrid metaheuristic algorithm that combines the specific advantages of four metaheuristics (harmony search, flower pollination algorithm, teaching‐learning‐based optimization and Jaya algorithm) is proposed for the optimization process. The results of the process showed that ATMDs are more effective for high values strike limitations, compared to TMDs. The feasibility and effectiveness of the optimum control method are also demonstrated on a full‐size 76‐story structure.

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“…Structural control devices can be classified into three categories: “passive control” (Froli et al., 2019; Narasimhan et al., 2006; Salvatore et al., 2021), “semi active control” (Gutierrez Soto & Adeli, 2019; Naderpoor & Taghikhany, 2022; Shi et al., 2021), and “active and hybrid control” (Bitaraf et al., 2012; Kim & Adeli, 2005a) systems. Recently, in the field of seismic protection, important advancements have been made (Gutierrez Soto & Adeli, 2018; Javidan & Kim, 2022; Xu et al., 2021), and researchers focused their attention on different vibration control technologies such as tuned mass dampers (Kayabekir et al., 2022; Kim & Adeli, 2005b). Base isolation devices have found their primary application in vibration control of buildings (Gutierrez Soto & Adeli, 2017; Kim & Adeli, 2005c; Li & Adeli, 2018) and bridges (Ghaedi et al., 2017; Kim & Adeli, 2005b).…”

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“…Each of these techniques has its own advantages and disadvantages. Therefore, studies on the integration of various techniques (Javadinasab Hormozabad et al., 2021; Karami & Akbarabadi, 2016; Kayabekir et al., 2022), application of machine learning techniques (Naderpoor & Taghikhany, 2022), and sustainable designs (Gutierrez Soto & Adeli, 2017a) have recently been conducted to develop vibration control systems. More detailed literature surveys on vibration control methods can be found in El‐Khoury and Adeli (2013) and Gutierrez Soto and Adeli (2017b).…”