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Vibration control enhancement in a full vehicle dynamic model by optimization of the controller's gain parameters.
- Source :
- Engineering Computations; 2024, Vol. 41 Issue 1, p259-286, 28p
- Publication Year :
- 2024
-
Abstract
- Purpose: In this paper, improvements in reducing transmitted accelerations in a full vehicle are obtained by optimizing the gain parameters of an active control in a roughness road profile. Design/methodology/approach: For a classically designed linear quadratic regulator (LQR) control, the vibration attenuation performance will depend on weighting matrices Q and R. A methodology is proposed in this work to determine the optimal elements of these matrices by using a genetic algorithm method to get enhanced controller performance. The active control is implemented in an eight degrees of freedom (8-DOF) vehicle suspension model, subjected to a standard ISO road profile. The control performance is compared against a controlled system with few Q and R parameters, an active system without optimized gain matrices, and an optimized passive system. Findings: The control with 12 optimized parameters for Q and R provided the best vibration attenuation, reducing significantly the Root Mean Square (RMS) accelerations at the driver's seat and car body. Research limitations/implications: The research has positive implications in a wide class of active control systems, especially those based on a LQR, which was verified by the multibody dynamic systems tested in the paper. Practical implications: Better active control gains can be devised to improve performance in vibration attenuation. Originality/value: The main contribution proposed in this work is the improvement of the Q and R parameters simultaneously, in a full 8-DOF vehicle model, which minimizes the driver's seat acceleration and, at the same time, guarantees vehicle safety. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 02644401
- Volume :
- 41
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Engineering Computations
- Publication Type :
- Academic Journal
- Accession number :
- 175802343
- Full Text :
- https://doi.org/10.1108/EC-04-2023-0178