Work

Vehicle Trajectory Adaptive Tracking Control Based on Variable Prediction Horizon

Year: 2025

Type: article

Abstract: The design of intelligent vehicle trajectory tracking controllers still has some problems, such as parameter uncertainty and time consumption. To improve the tracking accuracy of the trajectory tracking controller and reduce its computational complexity, an adaptive MPC trajectory tracking control method with a variable prediction horizon is proposed. Firstly, a three-degree-of-freedom vehicle dynamics model is constructed, and the design is improved based on the ordinary MPC controller. Secondly, several groups of different constant vehicle speeds are selected to compare the tracking effect of the ordinary MPC and the improved controller. Then, low speed (30 km/h) and high speed (100 km/h) are selected as representative speeds to solve the calculation time of the controller. The relationship between vehicle speed and prediction horizon is analyzed, and curve fitting is carried out. An adaptive trajectory tracking controller is designed. Finally, it is verified by CarSim and MATLAB/Simulink co-simulation. The results show that compared with ordinary MPC, the improved adaptive trajectory tracking controller can maintain good tracking accuracy and stability according to the speed change and improve the computational efficiency of the controller.

Source: Electronics

DOI: 10.3390/electronics14091769

Authors: Chuanyun Zhu, Kuiyang Wang, Yuyong Wang, Shihao Li

Institution: Jiangsu University of Technology

Language: English

Topic: Vehicle Dynamics and Control Systems

Subfield: Automotive Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,896