A trajectory tracking control during autonomous docking process for single-axle reconfigurable UGV modular unit using sliding mode prediction control

The reconfigurable modular unit (RMU) with single-axle dual-wheel configuration is the foundational component of the reconfigurable unmanned ground vehicle (RUGV), providing enhanced adaptability through independently controlled steering and driving capabilities. Achieving high-precision trajectory tracking during the autonomous docking process of RMUs is crucial to ensuring the scalability and flexibility of RUGV. This paper presents a trajectory tracking control strategy based on sliding mode predictive control (SMPC), specifically designed for RMU docking. To account for the unique structural characteristics and motion patterns of RMUs, this paper introduces generalized control variables, specifically the theoretical slip and radius angles, to describe the motion behavior. These variables are the foundation for developing a kinematic model suitable for control design. A dynamic simulation platform is developed to analyze the steady-state steering characteristics under different combinations of steering modes. The proposed SMPC controller adopts a prediction model in the Frenet coordinate system and incorporates a differential controller to compensate for tracking errors. Simulation results validate the effectiveness of the proposed approach, showing strong robustness under varying docking speeds and superior tracking accuracy compared with traditional methods. In particular, among the steering mode combinations evaluated, the differential steering + Ackermann steering mode delivers the highest tracking accuracy, effectively harnessing the structural advantages of the RMU.

Authors

Institutions

Publication Details

Journal
Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering
Published
2026-02-10
DOI
https://doi.org/10.1177/09544070251398576
Primary Topic
Vehicle Dynamics and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A trajectory tracking control during autonomous docking process for single-axle reconfigurable UGV modular unit using sliding mode prediction control

Feng Han, Tiezhen Wang, Wencheng Lv, Minghao Ma et al.
Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering
Vehicle Dynamics and Control Systems
article

A trajectory tracking control during autonomous docking process for single-axle reconfigurable UGV modular unit using sliding mode prediction control

Feng Han, Tiezhen Wang, Wencheng Lv, Minghao Ma, Xu Yang, Feiyu Wang
article en

Abstract

The reconfigurable modular unit (RMU) with single-axle dual-wheel configuration is the foundational component of the reconfigurable unmanned ground vehicle (RUGV), providing enhanced adaptability through independently controlled steering and driving capabilities. Achieving high-precision trajectory tracking during the autonomous docking process of RMUs is crucial to ensuring the scalability and flexibility of RUGV. This paper presents a trajectory tracking control strategy based on sliding mode predictive control (SMPC), specifically designed for RMU docking. To account for the unique structural characteristics and motion patterns of RMUs, this paper introduces generalized control variables, specifically the theoretical slip and radius angles, to describe the motion behavior. These variables are the foundation for developing a kinematic model suitable for control design. A dynamic simulation platform is developed to analyze the steady-state steering characteristics under different combinations of steering modes. The proposed SMPC controller adopts a prediction model in the Frenet coordinate system and incorporates a differential controller to compensate for tracking errors. Simulation results validate the effectiveness of the proposed approach, showing strong robustness under varying docking speeds and superior tracking accuracy compared with traditional methods. In particular, among the steering mode combinations evaluated, the differential steering + Ackermann steering mode delivers the highest tracking accuracy, effectively harnessing the structural advantages of the RMU.

Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering
Beijing Institute of Technology (CN)
Openalex Percentile: Top 62%
Vehicle Dynamics and Control Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A trajectory tracking control during autonomous docking process for single-axle reconfigurable UGV modular unit using sliding mode prediction control — Feng Han, Tiezhen Wang, et al. · Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering (2026) | TGRS Research Map | TGRS