Journal of System Simulation ›› 2024, Vol. 36 ›› Issue (10): 2300-2313.doi: 10.16182/j.issn1004731x.joss.23-0621

• Papers • Previous Articles    

Path Following Control and Simulation Analysis of Multi-articulated Vehicles

Zhao Yu, Yang Caijin, Wang Tanming, Xu Jing, Zhou Shuai   

  1. State Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, Chengdu 610031, China
  • Received:2023-05-25 Revised:2023-07-12 Online:2024-10-15 Published:2024-10-18
  • Contact: Yang Caijin

Abstract:

The structure of multi-articulated vehicle body limits the flexibility of the vehicle and causes the deviation of the rear vehicle. Taking the ideal articulation angle as the control target, a feedforward plus feedback path following control method is proposed, which realizes the precise path following of rear vehicle bodies by minimizing the deviation between the ideal articulation angle and the actual articulation angle. According to the geometric position relationship between the vehicle and the desired path, the traditional calculation method of the ideal articulation angle is improved from two perspectives of application range and error accumulation.Based on the ideal articulation angle of the vehicle and the applicable scope of the control method, a feedforward plus radial basis function (RBF) neural network PID feedback controller is designed, which do not depend on the specific model. The co-simulation platform TruckSim and MATLAB/Simulink is built to compare and analyze the path following performance of vehicles under different working conditions. The simulation results show that the proposed control method has good applicability and higher following accuracy in different working conditions, and effectively reduces the error accumulation of the rear vehicle.

Key words: multi-articulated vehicles, path following, ideal articulation angle, RBF neural network, co-simulation

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