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Optimal tuning of fuzzy parameters for structural motion control using multiverse optimizer
Author(s) -
Azizi Mahdi,
Ghasemi Seyyed Arash Mousavi,
Ejlali Reza Goli,
Talatahari Siamak
Publication year - 2019
Publication title -
the structural design of tall and special buildings
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.895
H-Index - 43
eISSN - 1541-7808
pISSN - 1541-7794
DOI - 10.1002/tal.1652
Subject(s) - fuzzy logic , controller (irrigation) , mathematical optimization , computer science , convergence (economics) , optimization problem , fuzzy control system , nonlinear system , control theory (sociology) , algorithm , mathematics , control (management) , artificial intelligence , physics , quantum mechanics , agronomy , economics , biology , economic growth
Summary In recent years, there is an increasing interest in optimization of structural control algorithms. Fuzzy logic controller is one of the most common and versatile control algorithms that is generally formulated based on the human knowledge and expert. Human knowledge and experience do not yield optimal control responses for a given structure, and tuning of the fuzzy parameters is necessary. This paper focuses on the optimization of a fuzzy controller applied to a seismically excited nonlinear building. In the majority of cases, this problem is formulated based on the linear behavior of the structure; however, in this paper, objective functions and the evaluation criteria are considered with respect to the nonlinear responses of the structures. Multiverse optimizer is a novel nature‐inspired optimization algorithm that is based on the three concepts of cosmology as white hole, black hole, and wormhole. This algorithm has fast convergence rate and can be utilized in continuous and discrete optimization problems. In this paper, the multiverse optimizer is considered as the optimization algorithm for optimization of the fuzzy controller. The performance of the selected algorithm is compared with eight different optimization algorithms. The results prove that the selected algorithm is able to provide very competitive results.