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المؤلفMuthalif, Asan G. A.
المؤلفRazali, M. Khusyaie M.
المؤلفNordin, N. H. Diyana
المؤلفHamid, Syamsul Bahrin Abdul
تاريخ الإتاحة2024-05-14T03:51:42Z
تاريخ النشر2021
اسم المنشورIEEE Access
المصدرScopus
المعرّفhttp://dx.doi.org/10.1109/ACCESS.2021.3080432
الرقم المعياري الدولي للكتاب21693536
معرّف المصادر الموحدhttp://hdl.handle.net/10576/54942
الملخصThe nonlinearity behaviour of magnetorheological fluid (MRF) can be described using a number of established models such as Bingham and Modified Bouc-Wen models. Since these models require the identification of model parameters, there is a need to estimate the parameters' value carefully. In this paper, an optimization algorithm, i.e., the Particle Swarm Optimization (PSO) algorithm, is utilized to identify the models' parameters. The PSO algorithm distinctively controls the best fit value by minimizing marginal error through root-mean-square error between the models and the empirical response. The validation of the algorithm is attained by comparing the resulting modified Bouc-Wen model behaviour using PSO against the same model's behaviour, identified using Genetic Algorithm (GA). The validation results indicate that the application of PSO is better in identifying the model parameters. Results from this estimation can be used to design a controller for various applications such as prosthetic limbs.
راعي المشروعThis work was supported in part by the Exploratory Research Grant Scheme from the Ministry of Higher Education Malaysia under Grant ERGS13-020-0053, and in part by the Qatar University-International Research Collaboration under Grant IRCC-2020-017.
اللغةen
الناشرInstitute of Electrical and Electronics Engineers Inc.
الموضوعgenetic algorithm
Magnetorheological fluid damper
parametric estimation
particle swarm optimization
العنوانParametric Estimation from Empirical Data Using Particle Swarm Optimization Method for Different Magnetorheological Damper Models
النوعArticle
الصفحات72602-72613
رقم المجلد9
dc.accessType Open Access


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