LAPSE:2023.13137
Published Article
LAPSE:2023.13137
An LPV-Based Online Reconfigurable Adaptive Semi-Active Suspension Control with MR Damper
February 28, 2023
Abstract
This study introduces an online reconfigurable road-adaptive semi-active suspension controller that reaches the performance objectives with satisfying the dissipativity constraint. The concept of the model is based on a nonlinear static model of the semi-active Magnetorheological (MR) damper with considering the bi-viscous and hysteretic behaviors of the damper. The input saturation problem has been solved by using the proposed method in the literature that allows the integration of the saturation actuator in the initial system to create a Linear Parameter Varying (LPV) system. The control input meets the saturation constraint; therewith, the dissipativity constraint is fulfilled. The online reconfiguration and adaptivity problem is solved by using an external scheduling variable that allows the trade-off between driving comfort and road holding/stability. The control design is based on the LPV framework. The proposed adaptive semi-active suspension controller is compared to passive suspension and Bingham model with Simulink simulation, and then the adaptivity of the controller is validated with the TruckSim environment. The results show that the proposed LPV controller has better performance results than the controlled Bingham and passive semi-active suspension model.
Keywords
adaptive control, adaptive semi-active suspension control, linear parameter varying (LPV), MR damper, reconfigurable control, semi-active suspension control
Suggested Citation
Basargan H, Mihály A, Gáspár P, Sename O. An LPV-Based Online Reconfigurable Adaptive Semi-Active Suspension Control with MR Damper. (2023). LAPSE:2023.13137
Author Affiliations
Basargan H: Department of Control for Transportation and Vehicle Systems, Budapest University of Technology and Economics, Muegyetem rkp. 3, H-1111 Budapest, Hungary [ORCID]
Mihály A: Systems and Control Laboratory, Institute for Computer Science and Control (SZTAKI), Eötvös Loránd Research Network (ELKH), 13-17 Kende Street, H-1111 Budapest, Hungary [ORCID]
Gáspár P: Systems and Control Laboratory, Institute for Computer Science and Control (SZTAKI), Eötvös Loránd Research Network (ELKH), 13-17 Kende Street, H-1111 Budapest, Hungary [ORCID]
Sename O: GIPSA-Lab, INPG, Université Grenoble Alpes, 11 Rue des Mathématiques, 38000 Grenoble, France [ORCID]
Journal Name
Energies
Volume
15
Issue
10
First Page
3648
Year
2022
Publication Date
2022-05-16
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en15103648, Publication Type: Journal Article
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LAPSE:2023.13137
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https://doi.org/10.3390/en15103648
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