Adaptive Robust Path Tracking Preview Control for Tractor-Trailer Trucks Considering Trailer Sway and Stochastic Disturbances

被引:0
|
作者
Liu, Yujie [1 ]
Yue, Ming [2 ,3 ]
Zhao, Xudong [4 ]
Zong, Guangdeng [5 ]
机构
[1] Dalian Univ Technol, Sch Mech Engn, Dalian 116024, Peoples R China
[2] Dalian Univ Technol, Sch Mech Engn, Dalian 116024, Peoples R China
[3] Dalian Univ Technol, State Key Lab High Performance Precis Mfg, Dalian 116024, Peoples R China
[4] Dalian Univ Technol, Sch Control Sci & Engn, Dalian 116024, Peoples R China
[5] Tiangong Univ, Sch Control Sci & Engn, Tianjin 300387, Peoples R China
基金
中国国家自然科学基金;
关键词
Stochastic processes; Adaptation models; Control systems; Adaptive control; Tires; Stability analysis; Robustness; Feedforward systems; Agricultural machinery; Wheels; Adaptive robust preview control; path tracking; tractor-trailer trucks; trailer sway; stochastic disturbances;
D O I
10.1109/TITS.2024.3524581
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This paper proposes an adaptive robust preview control method for path tracking in tractor-trailer trucks, aiming to effectively mitigate trailer sway and attenuate stochastic disturbances while adapting to variable vehicle velocity and path curvature. First, we establish the path tracking control system for the tractor-trailer truck, incorporating the hitch angle and hitch angle rate into the system state to minimize trailer sway. On this basis, an adaptive robust preview control method is developed, integrating feedforward and feedback control to improve tracking performance and robustness. The feedforward controller is designed to proactively minimize tracking errors. In the feedback control, an adaptive observer-based H-infinity robust feedback controller is developed to limit the effects of stochastic disturbances, where an innovative preview distance model, considering variable vehicle velocity and path curvature, is applied to achieve preview control. Then, based on the H-infinity theory, the design criterion of the proposed feedback controller is established, where bilinear matrix inequality (BMI) is transformed into linear matrix inequality (LMI) to solve the observer and controller gains. Additionally, the fuzzy algorithm is performed to enable the feedback controller to adapt to variable velocity. Finally, we evaluate the effectiveness of the proposed method using a hardware-in-the-loop platform. Simulation results confirm its superior robustness and performance compared to the existing baseline control method.
引用
收藏
页数:13
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