Gray skyhook predictive control of magnetorheological semi-active seat suspension with time delay
Auteur(s): |
Xiaomin Dong
Zhenyang Fei Zhiyuan Zhang Xiong Deng Pingyang Li Qinglin Liu |
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Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | Smart Materials and Structures, 19 octobre 2023, n. 11, v. 32 |
Page(s): | 115010 |
DOI: | 10.1088/1361-665x/acfcf7 |
Abstrait: |
Semi-active seat suspension with a magnetorheological (MR) damper has been a popular study issue in recent years. Since the response time delay of the MR damper can reduce the control effect and even make the vibration more severe, there is an urgent need to compensate for the response time delay. In this paper, gray prediction is introduced into the vibration control study of commercial vehicle seat suspension. A gray skyhook prediction controller is designed to compensate for the response time delay. This proposed controller does not rely heavily on controller parameter optimization and requires fewer state variables than other typical time delay compensation controllers. The mechanical property of the MR damper has been tested, modeled, and analyzed. A seat suspension dynamic model considering geometric nonlinearity is established based on the motion relationship between the components of the suspension. Subsequently, the effect of the response time delay on seat suspension vibration control has been verified by simulation. The results show that the control effect deteriorates significantly after considering the response time delay. Finally, prediction accuracy and vibration reduction performance of the designed gray skyhook predictive controller are verified by simulation and bench testing. The results illustrate that the gray skyhook predictive controller provides excellent time delay compensation and can significantly improve the ride comfort and handling stability of the driver. This study provides a reference for vibration control research of the MR seat suspension. |
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sur cette fiche - Reference-ID
10742592 - Publié(e) le:
28.10.2023 - Modifié(e) le:
28.10.2023