Event-Triggered-Based Distributed Formation Cooperative Tracking Control of Under-Actuated Unmanned Surface Vehicles With Input and State Quantization

For the maritime environment with limited communication bandwidth at sea, this paper investigates the distributed unmanned surface vehicles (USVs) formation tracking control problem with input and state quantization based on a time-varying threshold event-triggered mechanism. While ensuring that each follower USV can quickly form a formation and follow the virtual leader on the desired trajectory, it reduces the execution frequency of the controller, decreases the control amplitude, and saves communication resources. Firstly, a distributed event-triggered extended state observer (ESO) is designed to observe the virtual leader’s position information, and another ESO is used to estimate the quantized state information of each USV and the uncertainty terms existing in the model. Subsequently, the kinematic guidance law and the kinetic control laws based on a time-varying threshold event-triggered mechanism are proposed in quantized environment using the hierarchical design approach. In addition, the linear splitting of the input quantization makes the designed controller no longer require a priori information on the quantization parameters. Finally, the stability of the designed distributed USV formation tracking control system with input and state quantization based on the time-varying threshold event-triggered mechanism is demonstrated by input-to-state stability theory, and the absence of Zeno behavior in the proposed control strategy is also verified. Three sets of simulation experiments demonstrate the effectiveness and scientific validity of the proposed method.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Intelligent Transportation Systems
Published
2025-02-20
DOI
https://doi.org/10.1109/tits.2024.3524442
Citations
29
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
43.13

Funders

Controls
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article

Event-Triggered-Based Distributed Formation Cooperative Tracking Control of Under-Actuated Unmanned Surface Vehicles With Input and State Quantization

Jun Ning, C. L. Philip Chen, Yifan Ma
29 citations
IEEE Transactions on Intelligent Transportation Systems
Distributed Control Multi-Agent Systems
43.13
article

Event-Triggered-Based Distributed Formation Cooperative Tracking Control of Under-Actuated Unmanned Surface Vehicles With Input and State Quantization

Jun Ning, C. L. Philip Chen, Yifan Ma
article en
29 citations

Abstract

For the maritime environment with limited communication bandwidth at sea, this paper investigates the distributed unmanned surface vehicles (USVs) formation tracking control problem with input and state quantization based on a time-varying threshold event-triggered mechanism. While ensuring that each follower USV can quickly form a formation and follow the virtual leader on the desired trajectory, it reduces the execution frequency of the controller, decreases the control amplitude, and saves communication resources. Firstly, a distributed event-triggered extended state observer (ESO) is designed to observe the virtual leader’s position information, and another ESO is used to estimate the quantized state information of each USV and the uncertainty terms existing in the model. Subsequently, the kinematic guidance law and the kinetic control laws based on a time-varying threshold event-triggered mechanism are proposed in quantized environment using the hierarchical design approach. In addition, the linear splitting of the input quantization makes the designed controller no longer require a priori information on the quantization parameters. Finally, the stability of the designed distributed USV formation tracking control system with input and state quantization based on the time-varying threshold event-triggered mechanism is demonstrated by input-to-state stability theory, and the absence of Zeno behavior in the proposed control strategy is also verified. Three sets of simulation experiments demonstrate the effectiveness and scientific validity of the proposed method.

IEEE Transactions on Intelligent Transportation SystemsVol. 26(5)
Dalian Maritime University (CN), South China University of Technology (CN)
National Natural Science Foundation of China, Liaoning Revitalization Talents Program
Openalex Percentile: Top 0%
Distributed Control Multi-Agent Systems
43.13
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