An Enhanced Model‐Free Adaptive Control Algorithm for Heavy‐Duty Truck Formations With Time Delay and Constraint Handling

Engineering notes

Key topics: autonomous driving, control. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

ABSTRACT To address the challenges of longitudinal cooperative platoon control for multiple heavy‐duty trucks with time‐delay compensation under constraints, this paper presents a novel model‐free adaptive control algorithm termed TD‐cMFAC. The algorithm employs a pseudo partial derivative (PPD), a time‐varying parameter, to linearize the nonlinear dynamics of the multivehicle cooperative system using dynamic linearization techniques. Afterward, a dedicated TD‐cMFAC controller is then designed. To compensate for system time delays, a hybrid mechanism integrating a Smith predictor and a tracking differentiator (TD) is developed. The controller explicitly accounts for the input and output constraints inherent in practical control processes. The primary advantage of the TD‐cMFAC algorithm is its reliance solely on the input/output data of the multivehicle system throughout the control process while maintaining robust performance in the presence of time delays and constraints. Theoretical stability analysis confirms the robustness of the proposed method. By utilizing a MATLAB/Simulink and TruckSim co‐simulation interface, the effectiveness of the control strategy is demonstrated under complex driving is demonstrated, and its practical applicability is further validated through field tests conducted with an autonomous driving platform using heavy‐duty trucks on a test road in Tianjin, China.

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