A New Fractional Study on the Chaotic Vibration and State-Feedback Control of a Nonlinear Suspension System
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Date
2020
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Volume Title
Publisher
Pergamon-elsevier Science Ltd
Open Access Color
Green Open Access
No
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Publicly Funded
No
Abstract
This paper aims to establish a new fractional model to identify the complex behaviors of a magnetorheological suspension system under the road excitation of sinusoidal function. In the new model, we employ a recently introduced fractional operator with Mittag-Leffler kernel. To implement the model, we develop an efficient approximation scheme and discuss its stability and convergence analysis. We identify the complex behaviors by using the analysis of time-domain responses and phase portraits. The results show that the new fractional model has a strong capability to identify different characteristics of the system under investigation, including chaotic and nonchaotic behaviors. Finally, to avoid the chaotic vibration, a state-feedback controller is designed and its efficiency is proved by some simulation experiments. (C) 2019 Elsevier Ltd. All rights reserved.
Description
Ullah, Malik Zaka/0000-0003-2944-0352
ORCID
Keywords
Fractional Calculus, Mittag-Leffler Kernel, Mr Damper, Chaotic Vibration, State-Feedback Control, MR damper, Stability for nonlinear problems in mechanics, Mittag-Leffler kernel, Stabilization of systems by feedback, state-feedback control, Fractional ordinary differential equations, fractional calculus, Stability and convergence of numerical methods for ordinary differential equations, chaotic vibration
Turkish CoHE Thesis Center URL
Fields of Science
0103 physical sciences, 01 natural sciences
Citation
Ullah, M.Z...et al. (2020). "A New Fractional Study On the Chaotic Vibration and State-Feedback Control of A Nonlinear Suspension System", Chaos, Solitons and Fractals, Vol. 132.
WoS Q
Q1
Scopus Q
Q1

OpenCitations Citation Count
14
Source
Chaos, Solitons & Fractals
Volume
132
Issue
Start Page
109530
End Page
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CrossRef : 17
Scopus : 17
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Mendeley Readers : 7
SCOPUS™ Citations
17
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Web of Science™ Citations
17
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Page Views
4
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0.6888369
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