基于转向响应特性的智能车辆轨迹 跟踪双闭环控制

Translated title of the contribution: Dual Closed-Loop Control of Intelligent Vehicles Trajectory Tracking Based on Steering Response Characteristics

Bin Xu*, Dapeng Zhang, Haiyang Yang, Ziyong Han

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

The accuracy and robustness of intelligent vehicle trajectory tracking are important characteristic of vehicle motion control performance. Many Researches of tracking control based on path preview information have significantly improved vehicle performance. However, the insufficient response of the vehicle steering system have caused many difficulties for the vehicle to accurately track the reference trajectory based on the preview information in real time. To solve this problem, introducing state of the steering system in real time, a dual closed-loop trajectory tracking control structure was established to ensure the robustness of the intelligent vehicle trajectory tracking control algorithm for the insufficient response of the steering system. Concretely, in the outer loop of this structure, a model predictive control method was used to solve the optimal steering angle based on preview information. And in the inner loop of this structure, a PID method was used to design a feedback control law based on steering state error to compensate for insufficient steer­ing response. Coupling control input, the dual closed-loop structure can ensure the robust optimal tracking control of the vehicle. Finally, the effectiveness of the dual closed-loop control struc­ture was verified in Carsim and Simulink co-simulation.

Translated title of the contributionDual Closed-Loop Control of Intelligent Vehicles Trajectory Tracking Based on Steering Response Characteristics
Original languageChinese (Traditional)
Pages (from-to)706-712
Number of pages7
JournalBeijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume42
Issue number7
DOIs
Publication statusPublished - Jul 2022

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