Distributed Optimal Coordinated Control for Unmanned Surface Vehicles With Interleaved Periodic Event-Based Mechanism

In this article, we address the distributed optimal coordinated control (DOCC) problem for unmanned surface vehicles (USVs) suffering from limited network channels and communication interruptions. For networked USVs, ignoring network limitations can cause serious sailing incidents. Therefore, we dev...

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Veröffentlicht in:IEEE transactions on vehicular technology Jg. 73; H. 12; S. 18073 - 18086
Hauptverfasser: Huang, Bing, Peng, Hua, Zhang, Chengxi, Ahn, Choon Ki
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.12.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Channels
Communication channels
Control systems design
Design optimization
Eigenvalues and eigenfunctions
interleaved periodic event-based control
intermittent communication
Jamming
Laplace equations
Monitoring
Neural networks
Optimal control
Subsystems
Surface vehicles
Systems stability
Tracking control
Trajectory optimization
Unmanned surface vehicles (USVs)
Unmanned vehicles
Vectors
ISSN:0018-9545, 1939-9359
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Zusammenfassung:In this article, we address the distributed optimal coordinated control (DOCC) problem for unmanned surface vehicles (USVs) suffering from limited network channels and communication interruptions. For networked USVs, ignoring network limitations can cause serious sailing incidents. Therefore, we developed a DOCC design with a limited number of communication channels and a restricted communication range. The proposed optimal control system includes two subsystems: coordinated trajectory optimization and local trajectory tracking control. The first employs a delicately designed auxiliary system to determine the optimal solution for each USV. To address the scarcity and intermittency of communication channels, we also develop an intermittent interleaved periodic event-triggered mechanism (IIPETM) in the auxiliary system. The second subsystem adopts a neural network-based backstepping approach to achieve the tracking objective. Compared with the existing methods, the developed algorithm can interleave the triggering instants for different USVs and ensure system stability, even under communication interruptions. We demonstrate the effectiveness and superiority of the proposed scheme through numerical simulations of USVs.
Bibliographie:ObjectType-Article-1
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ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2024.3432736