Robust Path Tracking Control Design for Unmanned Agricultural Vehicles Using Adaptive Second-Order Sliding Mode

This paper focuses on the path tracking control for unmanned agricultural vehicles. To achieve high tracking accuracy and address the challenges of underactuation, we first design a second-order sliding mode controller. Then, to enable automatic gain adjustment, we develop an adaptive algorithm. Finally, we integrate these two components and conduct a rigorous stability analysis, which proves their finite-time stability. Simulation results on the CarSim platform demonstrate that our proposed approach significantly outperforms first- order sliding mode controller (FOSM) and PD controller in terms of accuracy and robustness, thereby greatly enhancing the autonomous navigation performance.

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Publication Details

Published
2025-05-17
DOI
https://doi.org/10.1109/yac66630.2025.11149744
Primary Topic
Bacterial Genetics and Biotechnology
Type
article
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article

Robust Path Tracking Control Design for Unmanned Agricultural Vehicles Using Adaptive Second-Order Sliding Mode

Bacterial Genetics and Biotechnology
article

Robust Path Tracking Control Design for Unmanned Agricultural Vehicles Using Adaptive Second-Order Sliding Mode

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Abstract

This paper focuses on the path tracking control for unmanned agricultural vehicles. To achieve high tracking accuracy and address the challenges of underactuation, we first design a second-order sliding mode controller. Then, to enable automatic gain adjustment, we develop an adaptive algorithm. Finally, we integrate these two components and conduct a rigorous stability analysis, which proves their finite-time stability. Simulation results on the CarSim platform demonstrate that our proposed approach significantly outperforms first- order sliding mode controller (FOSM) and PD controller in terms of accuracy and robustness, thereby greatly enhancing the autonomous navigation performance.

Jiangsu University (CN), Ministry of Agriculture and Rural Affairs (CN)
Zero hunger
Openalex Percentile: Top 37%
Bacterial Genetics and Biotechnology
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