A Study of Slope Path Tracking for Tracked Vehicles in Hilly Mountainous Areas

Boyang Wang, Zhaoguo Zhang, Faan Wang, Xinqi Liu, Kaiting Xie, Chang Ni

Research output: Contribution to journalConference articlepeer-review

Abstract

The paper proposes a tracked vehicle slope path track control algorithm based on MPC hilly mountainous area motor differential control. First, a tracked vehicle slope driving slip model is established to achieve the accurate estimation slope position. Second, the desired acceleration and desired angular acceleration are obtained as inputs by incorporating the intended linear and angular velocities, and the actual motivation required of the tracked vehicle when steering the vehicle on the slope is estimated by the MPC, and then the driving force is obtained as the actual control signal through the road surface response and kinematics solving to achieve the slope control of tracked vehicles. The actual control signal is obtained from the driving force through the road surface response and kinematics solution to realize the tracked vehicle slope path tracking control. The test outcomes demonstrate that our path tracking algorithm exhibits superior performance compared to the proportion integral differential (PID) control method during the vehicle's travel on a slope.

Original languageEnglish
JournalIEEE International Conference on Industrial Informatics (INDIN)
DOIs
Publication statusPublished - 2024
Externally publishedYes
Event22nd IEEE International Conference on Industrial Informatics, INDIN 2024 - Beijing, China
Duration: 18 Aug 202420 Aug 2024

Keywords

  • model predictive control (MPC)
  • path tracking
  • slope
  • tracked vehicle

Fingerprint

Dive into the research topics of 'A Study of Slope Path Tracking for Tracked Vehicles in Hilly Mountainous Areas'. Together they form a unique fingerprint.

Cite this

Wang, B., Zhang, Z., Wang, F., Liu, X., Xie, K., & Ni, C. (2024). A Study of Slope Path Tracking for Tracked Vehicles in Hilly Mountainous Areas. IEEE International Conference on Industrial Informatics (INDIN). https://doi.org/10.1109/INDIN58382.2024.10887376