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An LPV-Based Online Reconfigurable Adaptive Semi-Active Suspension Control with MR Damper

Author

Listed:
  • Hakan Basargan

    (Department of Control for Transportation and Vehicle Systems, Budapest University of Technology and Economics, Muegyetem rkp. 3, H-1111 Budapest, Hungary)

  • András Mihály

    (Systems and Control Laboratory, Institute for Computer Science and Control (SZTAKI), Eötvös Loránd Research Network (ELKH), 13-17 Kende Street, H-1111 Budapest, Hungary)

  • Péter Gáspár

    (Systems and Control Laboratory, Institute for Computer Science and Control (SZTAKI), Eötvös Loránd Research Network (ELKH), 13-17 Kende Street, H-1111 Budapest, Hungary)

  • Olivier Sename

    (GIPSA-Lab, INPG, Université Grenoble Alpes, 11 Rue des Mathématiques, 38000 Grenoble, France)

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.

Suggested Citation

  • Hakan Basargan & András Mihály & Péter Gáspár & Olivier Sename, 2022. "An LPV-Based Online Reconfigurable Adaptive Semi-Active Suspension Control with MR Damper," Energies, MDPI, vol. 15(10), pages 1-17, May.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:10:p:3648-:d:816908
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    Cited by:

    1. Péter Gáspár, 2022. "Control Design for Electric Vehicles," Energies, MDPI, vol. 15(12), pages 1-2, June.

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