Magnetorheological dampers are able to adapt their mechanical properties when subjected to a magnetic field which makes them a versatile option for controlling vibration in a vast number of industrial applications. This work proposes a numerical model of magnetorheological dampers using fuzzy sets as an alternative to the parametric models existing in the literature. Its main advantage is that it does not depend on highly complex mathematical modeling to represent the dynamic phenomena intrinsic to the system. Experimental data from tests previously performed with a LORD brand damper, model RD-8040-1, was used. A study of the modified Bouc-Wen Model and the Hysteretic Model was performed. Its parameters were updated by using the Differential Evolution algorithm. Then, the non-parametric model, based on neuro-fuzzy, was proposed. Through a comparison between the models, it was possible to confront the results of each model and observe that the fuzzy model was able to represent the damper in different conditions of electric current.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.