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Automotive Engineering ›› 2025, Vol. 47 ›› Issue (1): 55-66.doi: 10.19562/j.chinasae.qcgc.2025.01.006

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Research on Semi-Trailer Trajectory Tracking Based on Type-2 Fuzzy Logic Control

Peng Chen,Yingfeng Cai(),Haibo Yuan,Long Chen,Xiaoqiang Sun   

  1. Institute of Automotive Engineering,Jiangsu University,Zhenjiang 212013
  • Received:2024-06-02 Revised:2024-06-30 Online:2025-01-25 Published:2025-01-17
  • Contact: Yingfeng Cai E-mail:caicaixiao0304@126.com

Abstract:

Autonomous commercial semi-trailers can greatly improve trunk logistics efficiency. However, since the semi-trailer vehicle is a typical underdrive system, it is difficult to simultaneously achieve lateral trajectory tracking accuracy of both tractor and trailer under large curvature motion conditions. With the increase of vehicle speed and load, the transfer of the trailer centroid and load intensifies, causing a strong uncertain impact on the hinge point between the tractor and trailer and the deviation of the driving trajectory between the trailer and the tractor to further increase, which increases the trajectory tracking difficulty and affects its driving safety. To enhance the lateral safety of semi-trailer commercial vehicle tractor and trailer, a robust path tracking strategy based on a type-2 fuzzy control algorithm is proposed in this paper. Firstly, a seven-degree-of-freedom dynamic model of the semi-trailer vehicle is constructed in MATLAB/Simulink to accurately simulate the transverse and longitudinal motion dynamics of both tractor and trailer. Secondly, considering the coverage property of the input membership function to system uncertainty in type-2 fuzzy logic control theory, a type-2 fuzzy controller is designed to adjust the lateral tracking accuracy of both tractor and trailer simultaneously. To improve the precision of lateral trajectory tracking control under uncertain factors and reduce the difficulty of controller design, a particle swarm optimization algorithm is utilized to optimize the input membership function parameters of the type-2 fuzzy controller. Finally, vehicle trajectory tracking simulation is conducted under various speed and load conditions using a joint simulation platform of MATLAB/Simulink and TruckSim to validate the control strategy proposed in this paper, and the tracking accuracy is compared with those using traditional type-1 fuzzy control and preview control. The results show that the proposed type-2 fuzzy controller can significantly enhance the lateral trajectory tracking accuracy of the tractor and trailer under the condition that track curvature changes with double shifting lines.

Key words: autonomous, semi-trailer, trajectory tracking, type II fuzzy logic control