Articles | Volume 11, issue 2
https://doi.org/10.5194/ms-11-465-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.Novel semiactive suspension using a magnetorheological elastomer (MRE)-based absorber and adaptive neural network controller for systems with input constraints
Related subject area
Subject: Dynamics and Control | Techniques and Approaches: Experiment and Best Practice
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2021Cited articles
Cao, J., Liu, H., Li, P., and Brown, D. J.: State of the art in vehicle active
suspension adaptive control systems based on intelligent methodologies, IEEE
T. Intell. Transp., 9, 392–405,
https://doi.org/10.1109/TITS.2008.928244, 2008.
Chen, M., Ge, S. S., and Ren, B.: Adaptive tracking control of uncertain MIMO
nonlinear systems with input constraints, Automatica, 47, 452–465,
https://doi.org/10.1016/j.automatica.2011.01.025, 2011.
Choi, S. B., Li, W., Yu, M., Du, H., Fu, J., and Phu, D. X.: State of the Art on
Control Schemes for Smart Systems Featuring Magneto-Rheological Materials,
Smart Mater. Struct., 25, 043001,
https://doi.org/10.1088/0964-1726/25/4/043001, 2016.
Eem, S. H., Jung, H. J., and Koo, J. H.: Modeling of magneto-rheological elastomers
for harmonic shear deformation, IEEE T. Magn., 48, 3080–3083,
https://doi.org/10.1109/TMAG.2012.2205140, 2012.
El Majdoub, K., Ghani, D., Giri, F., and Chaoui, F. Z.: Adaptive semi-active
suspension of quarter-vehicle with magnetorheological damper, J. Dyn. Syst-T.
ASME, 137, 021010, https://doi.org/10.1115/1.4028314, 2015.