ARTICLE
A study of dynamic hysteresis model for a magnetorheological damper
1
Department of Aircraft Engineering, Air Force Institute of Technology, Taiwan R.O.C.
2
Department of Avionics Engineering, Air Force Academy, Taiwan R.O.C.
Submission date: 2022-11-20
Final revision date: 2023-01-30
Acceptance date: 2023-02-02
Online publication date: 2023-03-17
Publication date: 2023-04-28
Corresponding author
Journal of Theoretical and Applied Mechanics 2023;61(2):259-274
KEYWORDS
identificationLuGre modelmagnetorheological damperself-learning particleswarm optimization (SLPSO)sliding mode observer (SMO)
TOPICS
stability and vibrations systemsmechanics of materialsdynamics of machines, vehicles and flying structures
ABSTRACT
The paper proposes a new dynamic model based on the LuGre model and an electrical
equation to describe the hysteresis phenomenon for a magnetorheological (MR) damper.
In addition, a sliding mode observer (SMO) is proposed to estimate unmeasurable states
of the MR damper. The parameters of the MR damper are successfully identified by using
the self-learning particle swarm optimization (SLPSO) algorithm. The contributions of this
paper are: i) a new dynamic model based on the LuGre model and an electrical equation for
an MR damper is successfully formulated to fit for the hysteresis behavior, ii) the exerted
damping force can be practically adjusted by using input voltage for the dynamic model,
iii) the SMO is proposed to estimate the internal states and current, and iv) the unknown
parameters of the MR damper are successfully identified by using the SLPSO algorithm
with a numerical experiment.
REFERENCES (26)
1.
Ahmed K., Yan P., Li S., 2021, Duhem model-based hysteresis identification in piezo-actuated nano-stage using modified particle swarm optimization, Micromachines, 12, 3, 315.
2.
Ambhore N., Hivarale S., Pangavhane D., 2013, A study of Bouc-Wen model of magnetorheological fluid damper for vibration control, International Journal of Engineering Research and Technology (IJERT), 2, 2, 1-6.
3.
Andersen K.M., 2000, An elementary proof of Rayleigh’s principle, International Journal of Mathematical Education in Science and Technology, 31, 3, 449-453.
4.
Balamurugan L., Jancirani J., 2013, Application of a new modified parametric algebraic model for magnetorheological damper in vehicle semi-active suspension, International Journal of Automobile Engineering Research and Development, 3, 1, 1-14.
5.
Bartkowski P., Zalewski R., Chodkiewicz P., 2019, Parameter identification of Bouc-Wen model for vacuum packed particles based on genetic algorithm, Archives of Civil and Mechanical Engineering, 19, 322-333.
6.
Bhowmik S., 2011, Modelling and Control of Magnetorheological Damper: Real-Time Implementation and Experimental Verification, Department of Mechanical Engineering Technical University of Denmark.
7.
Boada M.J.L., Boada B.L., Diaz V., 2018, A novel inverse dynamic model for a magnetorheological damper based on network inversion, Journal of Vibration and Control, 24, 15, 3434-3453.
8.
Graczykowski C., Pawłowski P., 2017, Exact physical model of magnetorheological damper, Applied Mathematical Modelling, 47, 400-424.
9.
Ikhouane F., Rodellar J., 2005, On the hysteretic Bouc-Wen model, Nonlinear Dynamics, 42, 63-78.
10.
Ikhouane F., Rodellar J., 2007, Systems with Hysteresis: Analysis, Identification and Control Using the Bouc-Wen Model, John Wiley & Sons.
11.
Ismail M., Ikhouane F., Rodellar J., 2009, The hysteresis Bouc-Wen model, a survey, Archives of Computational Methods in Engineering, 16, 2, 161-188.
12.
Jiménez R., Álvarez-Icaza L., 2005, LuGre friction model for a magnetorheological damper, Structural Control and Health Monitoring, 12, 91-116.
13.
Li C., Yang S., Nguyen T.T., 2012, A self-learning particle swarm optimizer for global optimization problems, IEEE Transactions on Systems, Man, and Cybernetics – Part B: Cybernetics, 42, 3, 627-646.
14.
Metered H., 2010, Modelling and Control of Magnetorheological Dampers for Vehicle Suspension Systems, School of Mechanical, Aerospace and Civil Engineering, University of Manchester.
15.
Naz S., Raja M.A.Z., Mehmood A., Zameer A., Shoaib M., 2021, Neuro-intelligent networks for Bouc-Wen hysteresis model for piezostage actuator, The European Physical Journal Plus, 136, 396.
16.
Nguyen X.B., Komatsuzaki T., Truong H.T., 2022, Adaptive parameter identification of Bouc-Wen hysteresis model for a vibration system using magnetorheological elastomer, International Journal of Mechanical Sciences, 213, 106848.
17.
Niola V., Palli G., Strano S., Terzo M., 2019, Nonlinear estimation of the Bouc-Wen model with parameter boundaries: Application to seismic isolators, Computers and Structures, 222, 1-9.
18.
Pelliciari M., Marano G.C., Cuoghi T., Briseghella B., Lavorato D., Tarantino A.M., 2018, Parameter identification of degrading and pinched hysteretic systems using a modified Bouc-Wen model, Structure and Infrastructure Engineering, 14, 12, 1573-1585.
19.
Peng Y., Yang J., Li J., 2018, Parameter identification of modified Bouc-Wen model and analysis of size effect of magnetorheological dampers, Journal of Intelligent Material Systems and Structures, 29, 7, 1464-1480.
20.
Ramli M.H.M., Minh T.V., Chen X., 2019, Pseudoextended Bouc-Wen model and adaptive control design with applications to smart actuators, IEEE Transactions on Control Systems Technology, 27, 5, 2100-2109.
21.
Roussel R., Edelen A., Ratner D., Dubey K., Gonzalez-Aguilera J.P., Kim Y.K., Kuklev N., 2022a, Differentiable preisach modeling for characterization and optimization of accelerator systems with Hysteresis, arXiv preprint, arXiv:2202.07747.
22.
Roussel R., Edelen A., Ratner D., Dubey K., Gonzalez-Aguilera J.P., Kim Y.K., Kuklev N., 2022b, Differentiable Preisach modeling for characterization and optimization of particle accelerator systems with hysteresis, Physical Review Letters, 128, 20, 204801.
23.
Xu S., Wu Z., Wang J., Hong K., Hu K., 2022, Generalized regression neural network modeling based on inverse Duhem operator and adaptive sliding mode control for hysteresis in piezoelectric actuators, Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 236, 5, 1029-1037.
24.
Zalewski R., Nachman J., Shillor M., Bajkowski J., 2014, Dynamic model for a magnetorheological damper, Applied Mathematical Modelling, 38, 2366-2376.
25.
Zhao X., Wu S., Pan H., 2018, A hybrid model of magnetorheological dampers based on generalized hysteretic biviscous operators, Journal of Intelligent Material Systems and Structures, 29, 14, 2979-2985.
26.
Zhu H., Rui X., Yang F., Zhu W., Wei M., 2019, An efficient parameters identification method of normalized Bouc-Wen model for MR damper, Journal of Sound and Vibration, 448, 26, 146-158.
Share
RELATED ARTICLE
| eISSN: | 2543-6309 |
| ISSN: | 1429-2955 |
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
