Finite-Time Disturbance Compensation for Hierarchical Formation of Dual AGVs in Smart Ports

This paper proposes an integrated formation control framework with a finite-time nonlinear disturbance observer (FT-NDO) for automated guided vehicles (AGVs) operating in port environments, where constrained workspace, narrow formation spacing, and complex external disturbances pose significant challenges. An adaptive leader–follower formation strategy with dynamic inter-vehicle spacing is developed to enhance maneuverability during turning. Within a hierarchical control structure that decouples lateral and longitudinal dynamics, two sliding mode controllers (SMCs) are designed: (a) a lateral SMC that prioritizes heading accuracy, limiting yaw angle error to within ±2°; and (b) a nonsingular terminal SMC (NTSMC) for longitudinal control, improving error convergence speed compared to conventional SMC. An FT-NDO is further incorporated into both control loops to estimate and compensate for external disturbances in real time, achieving a disturbance estimation accuracy of over 95% and significantly attenuating the impact of environmental disturbances. Validation through simulation and physical experiment of a dual-AGV formation in a realistic port scenario demonstrates that the proposed approach restricts formation deviation to 0.015 m and maintains stable operation under various disturbance conditions. This study provides a practical solution for dual-AGV collaborative transportation in spatially constrained and dynamically disturbed environments, with direct implications for improving operational efficiency and safety in port logistics.

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Publication Details

Journal
Journal of Marine Science and Engineering
Published
2026-06-24
DOI
https://doi.org/10.3390/jmse14131166
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
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article

Finite-Time Disturbance Compensation for Hierarchical Formation of Dual AGVs in Smart Ports

Hui Li, Qiang Zhang, Dudu Guo, Zhengfang Xu et al.
Journal of Marine Science and Engineering
Distributed Control Multi-Agent Systems
article

Finite-Time Disturbance Compensation for Hierarchical Formation of Dual AGVs in Smart Ports

Hui Li, Qiang Zhang, Dudu Guo, Zhengfang Xu, Bo Yuan
article en

Abstract

This paper proposes an integrated formation control framework with a finite-time nonlinear disturbance observer (FT-NDO) for automated guided vehicles (AGVs) operating in port environments, where constrained workspace, narrow formation spacing, and complex external disturbances pose significant challenges. An adaptive leader–follower formation strategy with dynamic inter-vehicle spacing is developed to enhance maneuverability during turning. Within a hierarchical control structure that decouples lateral and longitudinal dynamics, two sliding mode controllers (SMCs) are designed: (a) a lateral SMC that prioritizes heading accuracy, limiting yaw angle error to within ±2°; and (b) a nonsingular terminal SMC (NTSMC) for longitudinal control, improving error convergence speed compared to conventional SMC. An FT-NDO is further incorporated into both control loops to estimate and compensate for external disturbances in real time, achieving a disturbance estimation accuracy of over 95% and significantly attenuating the impact of environmental disturbances. Validation through simulation and physical experiment of a dual-AGV formation in a realistic port scenario demonstrates that the proposed approach restricts formation deviation to 0.015 m and maintains stable operation under various disturbance conditions. This study provides a practical solution for dual-AGV collaborative transportation in spatially constrained and dynamically disturbed environments, with direct implications for improving operational efficiency and safety in port logistics.

Journal of Marine Science and EngineeringVol. 14(13)
Wuhan Polytechnic University (CN), Xinjiang University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Hubei Province
Openalex Percentile: Top 5%
Distributed Control Multi-Agent Systems
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