A preview driver model based on sliding-mode and fuzzy control for articulated heavy vehicle

To investigate the driver/articulated vehicle directional dynamics, combined with the structural characteristics of articulated heavy vehicles (AHVs) and preview driver model theory, a preview driver model suitable for AHV based on Sliding-mode control (SMC) and Fuzzy control is proposed and validat...

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Bibliographic Details
Published in:Meccanica (Milan) 2022-08, Vol.57 (8), p.1853-1878
Main Authors: Deng, Zhao Wen, Zhao, You Qun, Wang, Bao Hua, Gao, Wei, Kong, Xinxin
Format: Article
Language:English
Subjects:
Automotive Engineering
Center of gravity
Civil Engineering
Classical Mechanics
Dynamic structural analysis
Engineering
Fuzzy control
Heavy vehicles
Lateral displacement
Mechanical Engineering
Sliding mode control
Tracking control
Tracking errors
Yaw
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Summary:To investigate the driver/articulated vehicle directional dynamics, combined with the structural characteristics of articulated heavy vehicles (AHVs) and preview driver model theory, a preview driver model suitable for AHV based on Sliding-mode control (SMC) and Fuzzy control is proposed and validated. First, a linear yaw-plane model with three-degree-of freedom (3-DOF) for the AHV is built and verified. Second, a SMC driver model is designed, based on three-points preview following strategy and reference model of tractor yaw rate. Third, two different reference models of articulation angle are designed based on the double-center of gravity tracking the ideal path and trailer’s rear axle centre following the trajectory of the fifth wheel, respectively. Then, on the basis of the lateral displacement and yaw rate errors of the leading unit, a Fuzzy compensated driver model is designed based on the articulation angle tracking error control. Finally, the effectiveness and applicability of the preview driver model developed based on SMC and Fuzzy theory is validated and proved, using comparative analysis and numerous number simulations, at low and high speed, respectively.
ISSN:0025-6455
1572-9648
DOI:10.1007/s11012-022-01532-6